Purpose During the COVID-19 crisis, diversified attitudes and behaviors of structural equation modeling (SME) retailers were observed in using social media marketing that could have helped mitigate the adverse effects of this crisis on businesses. This paper aims to present a thorough investigation of these perceptions and limited acceptance of social media marketing among SME retailers in a developing country during a crisis. Design/methodology/approach The investigation was designed using a mixed-method design. A qualitative investigation, as the first part, explored SME retailers’ perceptions of the use of social media marketing when they were faced with mandatory lockdown that stifled their business activity. The insights from qualitative study and literature helped devise the second part of the study, a quantitative study using the technology acceptance model (TAM). Analysis of responses from a sample of SME retailers (n = 149) was done using SEM in this study. Findings In the qualitative study, SME retailers were found to have a varying outlook toward social media marketing. Some ventured into social media marketing while others were impeded by their limited understanding. The second (quantitative) study showed the general applicability of TAM such that perceived ease of use through perceived usefulness influenced SME retailers’ attitudes toward the usage of social media marketing during the COVID-19 crisis. An important finding in both studies was that business owners’ education level influenced their perceptions of social media marketing. Research limitations/implications The investigation, albeit a comprehensive one, was conducted in a particular market and for SME retailers. This opens avenues for conducting similar studies in other segments of entrepreneurs to generate insights based on comparative analysis across segments and scenarios. Originality/value Limited or no marketing in the physical marketplace amid lockdown meant almost an existential crisis for entrepreneurs, especially SME retailers, in developing countries during the COVID-19 crisis. While technology acceptance by SME retailers has been discussed in the literature, there are limited discourses on technology acceptance among entrepreneurs and SME retailers during a crisis. These findings from the COVID-19 crisis explicate the possibilities and limitations of technology usage as a means to mitigate challenges faced by entrepreneurs during a crisis.

Objective: Management of a patient presenting with a first seizure depends on the risk of additional seizures. In clinical practice, the recurrence risk is estimated by the treating physician using the neurological examination, brain imaging, a thorough history for risk factors, and routine scalp electroencephalogram (EEG) to detect abnormal epileptiform activity. The decision to use antiseizure medication can be challenging when objective findings are missing.There is a need for new biomarkers to better diagnose epilepsy following a first seizure. Recently, an EEG-based novel analytical method was reported to detect paroxysmal slowing in the cortical network of patients with epilepsy. The aim of our study is to test this method's sensitivity and specificity to predict epilepsy following a first seizure. Methods:We analyzed interictal EEGs of 70 patients admitted to the emergency department of a tertiary referral center after a first seizure. Clinical data from a follow-up period of at least 18 months were available. EEGs of 30 healthy controls were also analyzed and included. For each EEG, we applied an automated algorithm to detect paroxysmal slow wave events (PSWEs). Results:Of patients presenting with a first seizure, 40% had at least one additional recurring seizure and were diagnosed with epilepsy. Sixty percent did not report additional seizures. A significantly higher occurrence of PSWEs was detected in the first interictal EEG test of those patients who were eventually diagnosed with epilepsy. Conducting the EEG test within 72 h after the first seizure significantly increased the likelihood of detecting PSWEs and the predictive value for epilepsy up to 82%. Significance:The quantification of PSWEs by an automated algorithm can predict epilepsy and help the neurologist in evaluating a patient with a first seizure.

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Objective: The objective of this study was to evaluate the level of physical activity and its association with hemoglobin level among undergraduate students. Method and materials: A cross-sectional study was conducted on undergraduate students of Isra Institute Rehabilitation Sciences, Isra University Islamabad. The undergraduate students between 18- 25 years were included in the study. The hemoglobin level was evaluated through the hemoglobin-meter and physical activity through the International Physical Activity Questionnaires IPAQ-SF-7. The Pearson product-moment correlation was used to find association between physical activity and hemoglobin level. Results: The mean age of study participants was 21.10±1.76. Of the 400 participants, 22% participants had low level of physical activity, 46.25% participants had moderate level of physical activity and 31.75% participants had vigorous physical activity. The time spent in vigorous and moderate physical activity was significantly associated with the hemoglobin level (p<0.05) and sitting was negatively correlated with Hb (p<0.05). Conclusion: It was concluded that that levels of physical activity was significantly associated with the hemoglobin level. Keywords: Physical activity, hemoglobin, anemia.