ABSTRACT
Developing a sustainable and reliable photovoltaic (PV) energy system requires a comprehensive analysis of solar profiles and an accurate prediction of solar energy performance at the study site. Installing the PV modules with optimal tilt and azimuth angles has a significant impact on the total irradiance delivered to the PV modules. This paper proposes a comprehensive optimization model to integrate total irradiance models with the PV temperature model to find the optimal year-round installation parameters of PV modules. A novel integration between installation parameters and the annual average solar energy is presented, to produce the maximum energy output. The results suggest an increase in energy yields of 4% compared to the conventional scheme, where tilt angle is equal to the latitude and the PV modules are facing south. This paper uses a real-time dataset for the NEOM region in Saudi Arabia to validate the superiority of the proposed model compared to the conventional scheme, but it can be implemented as a scheme wherever real-time data are available.
ABSTRACT
Antibiotic resistance is a global health and development threat, especially during the Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) pandemic. Therefore, the current study was conducted to describe antibiotic usage and resistance among patients with COVID-19 in the intensive care unit (ICU) in Makkah, Saudi Arabia. In this cross-sectional study, only patients with positive COVID-19 status (42 patients) admitted to the ICU at the King Faisal Hospital were selected using a census sampling method. The susceptibility test of bacteria was carried out according to the standard protocol. The identified strains were tested in-vitro against several antibiotics drugs. Statistical analysis was performed using SPSS version 24. A total of 42 patients were included, with a mean age of 59.35 ± 18 years. Of them, 38.1% were males, and 61.9% were females. 35.7% have blood group O +. For age and blood groups, statistically significant associations were found between males and females, with p-values = 0.037 and 0.031, respectively. A large percentage (42.7%) of the obtained samples contained Klebsiella Pneumoniae; all bacteria were multidrug-resistance bacteria. Furthermore, 76.2% of bacteria were resistant to Ampicillin, 66.7% were resistant to Ciprofloxacin, 64.3% were resistant to Levofloxacin, 57.1% were resistant to Imipenem, and 57.1% were resistant to Moxifloxacin. On the contrary, among the 40 examined antibiotics, the effective antibiotics were Daptomycin, Linezolid, Mupirocin, Synercid, Teicoplanin, Vancomycin, and Nitrofurantoin. Our study demonstrates that antibiotic resistance is highly prevalent among ICU patients with COVID-19 at the King Faisal Hospital. Additionally, all bacteria were multidrug-resistance bacteria. Therefore, this high prevalence should be seriously discussed and urgently considered.