p-Tolyl bis­(p-tolyl­amido)phosphate

In the title compound, C21H23N2O2P, the P atom exhibits tetra­hedral coordination; the P—N bond lengths are relatively short [1.6297 (13) and 1.6424 (13) Å]. In the crystal, adjacent mol­ecules are linked by N—H⋯O hydrogen bonds into a zigzag chain running along the c axis

Frequency and Symptoms of Odontogenic Sinusitis: A Cross-Sectional Study

Background: Occasionally, chronic sinusitis has a dental origin. This Entity is usually resistant to common treatments and high clinical suspicion is necessary for its diagnosis. The symptoms of odontogenic sinusitis are similar to the symptoms caused by other causes of sinusitis, and so far no special symptoms have been introduced for it. In this study, we decided to measure the frequency of this disease and its symptoms. Aim: The aim of this study was to examine people with dental sinusitis in CT scan (with or without clear signs of sinusitis) and also to examine the prevalence of sinonasal symptoms in all patients as well as the group with odontogenic sinusitis. Methods: All candidates for septorhinoplasty in 2018 who came to the otorhinolaryngology clinic of Firoozgar Hospital, Tehran, Iran were included in the study. The coronal CT scan of the maxillary sinus of these people were checked for odontogenic sinusitis and at the same time the SNOT-22 sinonasal symptoms questionnaire was completed by the patients. Finally, the prevalence of odontogenic sinusitis and sinonasal symptoms among these patients have been examined. Results: Twenty-eight of 100 patients had evidence of chronic sinusitis. The prevalence of odontogenic sinusitis in the studied population was 17%. The average score of SNOT-22 was 34.23 ± 8.87 in patients with chronic sinusitis and 38.0 ± 10.45 in patients with odontogenic sinusitis. Conclusion: Sinonasal symptoms in patients with odontogenic sinusitis had a low prevalence and no special symptom can be considered to differentiate this disease from other causes of sinusitis

Acute Pulmonary Embolism in Post COVID-19 Infection, A Case Report

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Many centers have noticed a high number of venous thromboembolism (VTE) events among critically ill inpatients with COVID-19 pneumonia. COVID-19 infection is associated with high morbidity and mortality largely due to respiratory failure, with micro vascular pulmonary thrombosis or PE originating from the leg veins playing an additional important pathophysiological role. Having undiagnosed or untreated PE may worsen patient outcomes and use of empiric therapeutic anticoagulation in certain COVID patients who do not have PE/DVT has been advocated. Here, we report a cases of COVID-19, in which massive pulmonary thromboembolism (PTE) occurred a few days after discharge

Optimal power flow incorporating facts devices and stochastic wind power generation using krill herd algorithm

© 2020 by the authors. This paper deals with investigating the Optimal Power Flow (OPF) solution of power systems considering Flexible AC Transmission Systems (FACTS) devices and wind power generation under uncertainty. The Krill Herd Algorithm (KHA), as a new meta‐heuristic approach, is employed to cope with the OPF problem of power systems, incorporating FACTS devices and stochastic wind power generation. The wind power uncertainty is included in the optimization problem using Weibull probability density function modeling to determine the optimal values of decision variables. Various objective functions, including minimization of fuel cost, active power losses across transmission lines, emission, and Combined Economic and Environmental Costs (CEEC), are separately formulated to solve the OPF considering FACTS devices and stochastic wind power generation. The effectiveness of the KHA approach is investigated on modified IEEE‐30 bus and IEEE‐57 bus test systems and compared with other conventional methods available in the literature

Highly active Fe-doped ZIF-8 nanocatalyst in electrochemical degradation of pharmaceutical pollutant in neutral environment

In this study, zeolitic imidazolate framework (ZIF-8) nanocatalyst was synthesized by the thermal solvent method and doped by Fe species through wet impregnation technique. The nanocatalysts were applied for the degradation of Phenazopyridine Hydrochloride (PHP) through the heterogeneous Electro-Fenton (HEF) process. The nanocatalysts were characterized by XRD, BET-BJH, FT-IR, FE-SEM, TEM, and acidimetric-alkalimetric titration techniques. The results showed the high surface area (1335 m2g-1) and homogenous dispersion of Fe species. The influence of different operating conditions was investigated, including pH level, nanocatalyst concentration, applied current, and PHP concentration. The optimum conditions for the HEF system over the Fe-ZIF-8 nanocatalyst were pH=7, 0.2 g L-1 of the Fe-ZIF-8 nanocatalyst, 100 mA, and 10 ppm of PHP concentration, which resulted in 99% PHP removal. The developed nanocatalyst had high reusability for the PHP removal in the HEF process. The results confirm the high potential of ZIF-8 nanocatalyst for pharmaceutical wastewater treatment through the HEF process

Origin of training effect of exchange bias in Co/CoO due to irreversible thermoremanent magnetization of the magnetically diluted antiferromagnet

The irreversible thermoremanent magnetization of a sole, magnetically diluted epitaxial antiferromagnetic Co$_{1-y}$O(100) layer is determined by the mean of its thermoremanent magnetizations at positive and negative remanence. During hysteresis-loop field cycling, thermoremanent magnetization exhibits successive reductions, consistent with the training effect (TE) of the exchange bias measured for the corresponding Co$_{1-y}$O(100)/Co bilayer. The TE of exchange bias is shown to have its microscopic origin in the TE of the irreversible thermoremanent magnetization of the magnetically diluted AFM

Multi-objective optimal reactive power planning under load demand and wind power generation uncertainties using ε-constraint method

© 2020 by the authors. This paper presents an improved multi-objective probabilistic Reactive Power Planning (RPP) in power systems considering uncertainties of load demand and wind power generation. The proposed method is capable of simultaneously (1) reducing the reactive power investment cost, (2) minimizing the total active power losses, (3) improving the voltage stability, and (4) enhancing the loadability factor. The generators\u27 voltage magnitude, the transformer\u27s tap settings, and the output reactive power of VAR sources are taken into account as the control variables. To solve the probabilistic multi-objective RPP problem, the -constraint method is used. To test the effectiveness of the proposed approach, the IEEE 30-bus test system is implemented in the GAMS environment under five different conditions. Finally, for a better comprehension of the obtained results, a brief comparison of outcomes is presented