Optimal Currency-Peg for an Oil-Exporting Country: The Case of Saudi Arabia

Economic

Safety and efficacy of Favipiravir in moderate to severe SARS-CoV-2 pneumonia

Background: We examined the safety and efficacy of a treatment protocol containing Favipiravir for the treatment of SARS-CoV-2. Methods: We did a multicenter randomized open-labeled clinical trial on moderate to severe cases infections of SARS-CoV-2. Patients with typical ground glass appearance on chest computerized tomography scan (CT scan) and oxygen saturation (SpO2) of less than 93 were enrolled. They were randomly allocated into Favipiravir (1.6 gr loading, 1.8 gr daily) and Lopinavir/Ritonavir (800/200 mg daily) treatment regimens in addition to standard care. In-hospital mortality, ICU admission, intubation, time to clinical recovery, changes in daily SpO2 after 5 min discontinuation of supplemental oxygen, and length of hospital stay were quantified and compared in the two groups. Results: 380 patients were randomly allocated into Favipiravir (1 9 3) and Lopinavir/Ritonavir (1 8 7) groups in 13 centers. The number of deaths, intubations, and ICU admissions were not significantly different (26, 27, 31 and 21, 17, 25 respectively). Mean hospital stay was also not different (7.9 days SD = 6 in the Favipiravir and 8.1 SD = 6.5 days in Lopinavir/Ritonavir groups) (p = 0.61). Time to clinical recovery in the Favipiravir group was similar to Lopinavir/Ritonavir group (HR = 0.94, 95% CI 0.75 � 1.17) and likewise the changes in the daily SpO2 after discontinuation of supplemental oxygen (p = 0.46) Conclusion: Adding Favipiravir to the treatment protocol did not reduce the number of ICU admissions or intubations or In-hospital mortality compared to Lopinavir/Ritonavir regimen. It also did not shorten time to clinical recovery and length of hospital stay. © 2021 Elsevier B.V

Twenty-four-hour intraocular pressure and ocular perfusion pressure characteristics in newly diagnosed patients with normal tension glaucoma

PurposeTo determine the mean 24-h intraocular pressure (IOP) and mean ocular perfusion pressure (MOPP) characteristics of newly diagnosed, previously untreated, Caucasian, normal tension glaucoma (NTG) patients and to identify relationships between these features and visual field (VF) loss at diagnosis.MethodsConsecutive newly diagnosed NTG patients underwent 24-h habitual IOP and blood pressure (BP) monitoring. Parameters from pooled measurements obtained in the sitting (0800-2200 hours) and supine (1200-0600 hours) positions were compared and associations were sought with VF mean deviation (MD) and pattern standard deviation (PSD).ResultsSixty-two Caucasian NTG patients (24 men and 38 women) successfully completed circadian IOP and BP monitoring. In habitual position, 8 subjects (12.9%) exhibited a diurnal acrophase, 42 subjects (67.7%) demonstrated a nocturnal acrophase, one subject (1.6%) showed a flat rhythm and 11 patients (17.7%) revealed a biphasic/polyphasic rhythm. Nighttime MOPP values (supine position) were significantly greater than diurnal values (sitting position); (P<0.001). No association could be demonstrated between glaucomatous damage, as indicated by VF parameters, and either mean habitual 24-h IOP (P=0.20 and P=0.12 for MD and PSD, respectively), or habitual 24-h MOPP (P=0.96 and 0.29, for MD and PSD, respectively).ConclusionsIn this cohort of Caucasian NTG patients, most patients exhibited a nocturnal IOP acrophase when evaluated in a habitual position. No association was found between 24-h IOP or MOPP and VF damage.Eye advance online publication, 29 July 2016; doi:10.1038/eye.2016.168

Nickel Nanoparticles Decorated on Glucose-Derived Carbon Spheres as a Novel, Non-Palladium Catalyst for Epoxidation of Olefin

Carbon spheres supporting nickel nanoparticles (NPs), generated by the integration of hydrothermal and microwave irradiation techniques, catalyzed the epoxidation of 1-octene, cyclooctene, styrene, allyl alcohol, and cyclohexene. The average particle sizes of the carbon spheres (CSs) and nickel oxide species immobilized on the CSs were 240 nm and 26 nm, respectively. The fabricated composites incorporating nickel NPs showed higher activity in the cyclohexene epoxidation process. The cyclohexene conversion was enhanced by raising the Ni loading to 10%. Within 14 h, the cyclohexene conversion had grown to 98%. This robust catalytic activity can be attributed to the efficient distribution of Ni species on the CSs, the facile lowering of the surface, and the development of uniformly nanosized species. The composite exhibited good recyclability across at least five cycles (which is not a simple task involving nickel-nanoparticle-based catalysts that are employed in water), and no nickel species leached into the solution, making the total system environmentally benign and cost-effective

Hydrometeorological Drought Forecasting in Hyper-Arid Climates Using Nonlinear Autoregressive Neural Networks

Drought forecasting is an essential component of efficient water resource management that helps water planners mitigate the severe consequences of water shortages. This is especially important in hyper-arid climates, where drought consequences are more drastic due to the limited water resources and harsh environments. This paper presents a data-driven approach based on an artificial neural network algorithm for predicting droughts. Initially, the observed drought events in the State of Kuwait were tested for autocorrelation using the correlogram test. Due to the cyclic nature of the observed drought time series, nonlinear autoregressive neural networks (NARs) were used to predict the occurrence of drought events using the Levenberg&ndash;Marquardt algorithm to train the NAR models. This approach was tested for the forecasting of 12- and 24-month droughts using the recently developed precipitation index (PI). Four statistical measures were used to assess the model&rsquo;s performance during training and validation. The performance metrics indicated that the drought prediction was reliable, with Nash&ndash;Sutcliffe values of 0.761&ndash;0.878 during the validation period. Additionally, the computed R2 values for model forecasts ranged between 0.784&ndash;0.883, which indicated the quality of the model predictions. These findings contribute to the development of more efficient drought forecasting tools for use by water managers in hyper-arid regions