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This paper addresses the issues of slug detection and characterization in air-water two-phase flow in a vertical pipeline. A novel non-invasive measurement technique using continuous-wave Doppler ultrasound (CWDU) and bandpass power spectral density (BPSD) is proposed for multiphase flow applications and compared with the more established gamma-ray densitometry measurement. In this work, analysis using time-frequency analysis of the CWDU is performed to infer the applicability of the BPSD method for observing the slug front and trailing bubbles in a multiphase flow. The CWDU used a piezo transmitter/receiver pair with an ultrasonic frequency of 500 kHz. Signal processing on the demodulated signal of Doppler frequency was done using the Butterworth bandpass filter on the power spectral density which reveals slugs from background bubbles. The experiments were carried out in the 2” vertical pipeline-riser at the process system engineering laboratory at Cranfield University. The 2-inch test facility used in this experiment is made up of a 54.8 mm internal diameter and 10.5 m high vertical riser connected to a 40 m long horizontal pipeline. Taylor bubbles were generated using a quick-closing air valve placed at the bottom of the riser underwater flow, with rates of 0.5 litres/s, 2 litres/s, and 4 litres/s. The CWDU spectrum of the measured signal along with the BPSD method is shown to describe the distinctive nature of the slugs

Coronavirus disease 2019 (COVID-19) has emerged as an important cause of morbidity and mortality worldwide. The aim of this study is to identify the clinical predictors of mortality among patients with COVID-19 pneumonia during first and second waves in a treatment center in northwestern Nigeria. This was a retrospective cohort study of 195 patients hospitalized with COVID-19 between April 2020 to March 2021 at a designated COVID-19 isolation center in Kano State, Northwest Nigeria. Data were summarized using frequencies and percentages. Unadjusted odds ratios and 95% confidence intervals and p-values were obtained. To determine independent determinants of mortality, we performed a stepwise multivariate logistic regression model. Of 195 patients studied, 21(10.77%) patients died. Males comprised 158 (81.03%) of the study population. In the adjusted stepwise logistic regression analysis, age>64 years (OR = 9.476, 95% CI: 2.181-41.165), second wave of the pandemic (OR = 49.340, 95% CI:6.222-391.247), cardiac complications (OR = 24.984, 95% CI: 3.618-172.508), hypertension (OR = 5.831, 95% CI:1.413-24.065) and lowest systolic blood pressure while on admission greater than or equal to 90mmHg were independent predictors of mortality (OR = 0.111, 95%CI: 0.021-0.581). Strategies targeted to prioritize needed care to patients with identified factors that predict mortality might improve patient outcome.

Coronavirus disease 2019 (COVID-19) has emerged as an important cause of morbidity and mortality worldwide. This was a retrospective cohort study of 195 patients hospitalized with COVID-19 between April 2020 to March 2021 at a designated COVID-19 isolation center in Kano State, Northwest Nigeria. Data were summarized using frequencies and percentages. Unadjusted odds ratios and 95% confidence intervals and p-values were obtained. To determine independent determinants of mortality, we performed a stepwise multivariate logistic regression model. Of 195 patients studied, 21(10.77%) patients died. Males comprised 158 (81.03%) of the study population. In the adjusted stepwise logistic regression analysis, age>64 years (OR = 9.476, 95% CI: 2.181-41.165), second wave of the pandemic (OR = 49.340, 95% CI:6.222-391.247), cardiac complications (OR = 24.984, 95% CI: 3.618-172.508), hypertension (OR = 5.831, 95% CI:1.413-24.065) and lowest systolic blood pressure while on admission greater than or equal to 90mmHg were independent predictors of mortality (OR = 0.111, 95%CI: 0.021-0.581). Strategies targeted to prioritize needed care to patients with identified factors that predict mortality might improve patient outcome.

Coronavirus disease 2019 (COVID-19) has emerged as an important cause of morbidity and mortality worldwide. This was a retrospective cohort study of 195 patients hospitalized with COVID-19 between April 2020 to March 2021 at a designated COVID-19 isolation center in Kano State, Northwest Nigeria. Data were summarized using frequencies and percentages. Unadjusted odds ratios and 95% confidence intervals and p-values were obtained. To determine independent determinants of mortality, we performed a stepwise multivariate logistic regression model. Of 195 patients studied, 21(10.77%) patients died. Males comprised 158 (81.03%) of the study population. In the adjusted stepwise logistic regression analysis, age>64 years (OR = 9.476, 95% CI: 2.181-41.165), second wave of the pandemic (OR = 49.340, 95% CI:6.222-391.247), cardiac complications (OR = 24.984, 95% CI: 3.618-172.508), hypertension (OR = 5.831, 95% CI:1.413-24.065) and lowest systolic blood pressure while on admission greater than or equal to 90mmHg were independent predictors of mortality (OR = 0.111, 95%CI: 0.021-0.581). Strategies targeted to prioritize needed care to patients with identified factors that predict mortality might improve patient outcome.