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Objective: To compare NEDOCS with ICMED in predicting clinicians' concerns regarding crowding in the Emergency Department of a tertiary care hospital in Pakistan. Study Design: Prospective comparative study. Place and Duration of Study: Accident & Emergency Department, Pak Emirates Military Hospital, Rawalpindi Pakistan, from Dec 2021 to Jan 2022. Methodology: This study was conducted at the Accident and Emergency Department over 14 different days, 30 data sets of 3-hour intervals each were collected using the NEDOCS and ICMED proforma. NEDOCS Scores and ICMED scores were calculated. In addition, perceptions of the staff regarding crowding and danger to the patient's status were recorded on Visual Analogue scales. Results: The mean recorded NEDOCS score was 577.94±251.57, with 29 'extremely overcrowded' and 1 'overcrowded' data set.The mean ICMED score was 2.86±0.83. Twenty-four (80%) sets did not have crowding, with only six (20%) sets being categorized as 'crowded'. The NEDOCS score had a moderately positive correlation with the crowding perception of the staff (Correlation coefficient (r)=0.593). Conclusion: NEDOCS was a more suitable measure for recording ED crowding in Pakistan, as it recorded the quantitative component of waiting time. ICMED, on the other hand, only recorded waiting time on a binary scale, with the waiting time impact not translated fully on the total score.

Objective: To determine the association of body mass index with the severity of COVID-19 pneumonia in hospitalized patients. Study Design: Cross-sectional study. Place and Duration of Study: Pak Emirates Military Hospital, Rawalpindi Pakistan, form May to Jun 2021. Methodology: Patients diagnosed with COVID-19 pneumonia on PCR and chest imaging and admitted to our hospital were included in the study. Body mass index was calculated on the first day of hospital admission, and they were followed up for two weeks during the disease. Increased oxygen demand, duration of admission, CT severity score and use of non-invasive ventilation were compared in patients with normal and increased body mass index. Results: A total of 800 COVID-19 patients admitted to the hospital were included in the final analysis. The mean age of the study participants was 41.36±4.55 years. Out of 800 patients, 337(42.1%) had normal BMI, 420(52.5%) were classed in the category of overweight and 43(5.4%) were obese. Furthermore, it was seen that increased demand for oxygen, high CT severity score and longer duration of hospital admission had a statistically significant relationship (p-value

Ultraviolet fluorescence (UVF) imaging is a widely used technique to analyze encapsulant discoloration, which is one of the prominent degradation modes in photovoltaic (PV) modules. Conventionally, UVF is done during nighttime or in a dark room, but performing UVF imaging during nighttime causes several inconveniences including safety due to snakes and other animals and inconvenient scheduling issues for the plant owners. Similarly, performing UVF imaging indoors requires dismounting the modules from the racks and moving them to the laboratory, which are labor-intensive and time-consuming tasks and could damage the module or may cause the energy loss due to partial/complete plant/array shutdown. Moreover, the manufacturer/installer warranty may be voided if the modules are removed from the racks. An outdoor UVF setup that can be used during the daylight can be a better alternative to the indoor or nighttime setup, provided it ensures there is no leakage of ambient light into the covered testing structure. We propose a unique, portable, and user-friendly outdoor UVF setup design that can tackle the issue of the ambient light leaking in, give uniform UV light, and provide enough room to accommodate the UV light source and camera to capture module images. We also classify the encapsulant discoloration into three classes depending on the discoloration intensity level. Furthermore, using the image processing technique, the percentage of browning was calculated in each cell/module.

Objectives To compare image quality on computed tomographic (CT) images acquired with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) techniques in CT kidney/ureter/bladder (KUB) examination. Methods Eighteen patients underwent standard protocol CT KUB at our institution. The same raw data were reconstructed using FBP, ASIR and MBIR. Objective [mean image noise, contrast-to-noise ratio (CNR) for kidney and mean attenuation values of subcutaneous fat] and subjective image parameters (image noise, image contrast, overall visibility of kidneys/ureters/bladder, visibility of small structures, and overall diagnostic confidence) were assessed using a scoring system from 1 (best) to 5 (worst). Results Objective image measurements revealed significantly less image noise and higher CNR and the same fat attenuation values for the MBIR technique (P 0.05), while there was a significant difference between ASIR vs. MBIR (P