Neural Network-based Finite-time Control of Nonlinear Systems with Unknown Dead-zones: Application to Quadrotors

Over the years, researchers have addressed several control problems of various classes of nonlinear systems. This article considers a class of uncertain strict feedback nonlinear system with unknown external disturbances and asymmetric input dead-zone. Designing a tracking controller for such system is very complex and challenging. This article aims to design a finite-time adaptive neural network backstepping tracking control for the nonlinear system under consideration. In addition,  all unknown disturbances and nonlinear functions are lumped together and approximated by radial basis function neural network (RBFNN). Moreover, no prior  information about the boundedness of the dead-zone parameters is required in the controller design. With the aid of a Lyapunov candidate function, it has been shown that the tracking errors converge near the origin in finite-time. Simulation results testify that the proposed control approach can force the output to follow the reference trajectory in a short time despite the presence of  asymmetric input dead-zone and external disturbances. At last, in order to highlight the effectiveness of the proposed control method, it is applied to a quadrotor unmanned aerial vehicle (UAV)

RAPD-PCR analysis of some species of Euphorbia grown in University of Baghdad Campus in Jadiriyah

This study attempts to identify species of Euphorbia (Euphorbia peplus, Euphorbia helioscopia, Euphorbia granulata and Euphorbia hirta) grown in University of Baghdad Campus in Jadiriyah and determine the genetic polymorphism among them by using DNA markers generated by polymerase chain reaction (PCR). Total genomic DNA of species studied was extracted from dry seeds by using commercial kit. Molecular analysis was performed by using nine random markers in random amplified polymorphic DNA (RAPD-PCR) technique. RAPD-PCR analyses based on three primers A13, C05 and D20 gave results in term of amplification and polymorphisim for the four species studied. The genetic polymorphisms value of each primer was determined and ranged between 47 to 84%; primer A13 produced the highest percent of genetic polymorphism compared with primer C05. RAPD-PCR technique confirmed the isolation of the four species of Euphorbia obviously.Key words: Euphorbia spp., random markers in random amplified polymorphic DNA (RAPD-PCR), monomorphic, polymorphic, random primers

Biomarker potential of C-peptide for screening of insulin resistance in diabetic and non-diabetic individuals

Insulin resistance is a hallmark feature of type-2 diabetes mellitus (T2DM). We determined the homeostatic model assessment insulin resistance (HOMA-IR) and evaluated its association with C-peptide, insulin, fasting blood glucose (FBG) and glycated hemoglobin (HbA1c) in T2DM patients and non-diabetic subjects. This study comprised a total of 47 T2DM patients and 38 non-diabetic controls. Venous blood samples from all the subjects were collected and sera were analyzed for FBG, HbA1c, insulin and C-peptide using an autoanalyzer. HOMA-IR was calculated using the following equation: HOMA-IR = fasting insulin (µU/ml) × fasting glucose (mmol/L)/22.5. There was a significant increase in the levels of FBG and HbA1c in diabetic patients. Although the levels of C-peptide and insulin did not differ significantly between the two groups, a significant increase in HOMA-IR was observed in T2DM patients. Both insulin and C-peptide were significantly correlated with HOMA-IR. In conclusion, C-peptide may serve as a simple and convenient predictor of HOMA-IR. Keywords: Insulin resistance, Diabetes, C-peptide, Fasting blood glucose, HbA1c, Biomarke

COVID-19-induced encephalitis: a case report of a rare presentation with a prolonged electroencephalogram

Encephalitis is one of the rare complications of coronavirus disease 2019 (COVID-19) that can be missed and confused with other causes of encephalitis. There was a 36-year-old male known to have glucose-6 phosphate dehydrogenase deficiency, who was brought to the emergency department with fever and confusion of one-week duration. Altered mental status work-up, including cerebrospinal fluid analysis, was done and turned out to be nondiagnostic. Multiple prolonged video-electroencephalographic recordings were done and showed different abnormalities suggestive of encephalitis. The diagnosis of COVID-19-induced encephalitis was made by exclusion of other encephalitis-related etiologies in the presence of a positive COVID-19 polymerase chain reaction (PCR) test, and treatment was initiated accordingly. Over a period of three weeks, the patient showed progressive improvement and was discharged home with regular follow-up in the neurology clinic. Upon follow-up in the clinic, the patient was fully independent but with multiple abnormal electroencephalographic recordings showing generalized encephalopathy with no epileptic discharges

Outdoor/Indoor Contaminant Transport by Atmospheric Dust and Aerosol at an Active Smelter Site

Activities associated with mining operations including smelting, ore handling, and mine tailings management have been identified as sources of dust and aerosol that may contain metal and metalloid contaminants, such as lead (Pb) and arsenic (As). Previous studies on contaminant transport have concentrated on the potential impact of these particulate emissions in outdoor environments. The purposes of this study were (i) to quantify the effect of dust and aerosol particle size on contaminant transport from outdoor-to-indoor environments and (ii) to document the changes in particle chemical composition during transport through the outdoor/indoor barrier. Outdoor and indoor particulate samples were collected at a high school equipped with mechanical air filtration systems from 2016 to 2019. The school is located near a set of mine tailings and an active copper smelter in Hayden, Arizona. Particle size segregated samples were collected using a ten-stage micro-orifice uniform deposit impactor (MOUDI). Results show that airborne fine particles (aerodynamic diameters less than 1 micron) can penetrate to the indoor environment but in a reduced amount due to mechanical filtration. Aerosol in the fine fraction particulate air concentrations was around 50% of the corresponding outdoor values, but their mass concentration of contaminants was similar to outdoor values. Indoor coarse particles (> 1 micron) comprised close to 20% of the levels found in outdoor coarse particles. These results highlight the need to consider the impact of particle diameter when assessing indoor exposure and potential health effects in communities living under the direct influence of mining and smelter activities. © 2021, The Author(s), under exclusive licence to Springer Nature Switzerland AG.12 month embargo; published: 22 May 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]