The paper presents automatic control of an aircraft in the longitudinal channel during automatic landing. There are two crucial components of the system presented in the paper: a vision system and an automatic landing system. The vision system processes pictures of dedicated on-ground signs which appear to an on-board video camera to determine a glide path. Image processing algorithms used by the system were implemented into an embedded system and tested under laboratory conditions according to the hardware-in-the-loop method. An output from the vision system was used as one of the input signals to an automatic landing system. The major components are control algorithms based on the fuzzy logic expert system. They were created to imitate pilot actions while landing the aircraft. Both systems were connected with one another for cooperation and to control an aircraft model in a simulation environment. Selected results of tests presenting control efficiency and precision are shown in the final section of the paper.

The paper presents the concept of a component of an aircraft’s automatic flight control system, controlling the airplane when in longitudinal motion (i.e., pitch angle, sink rate, airspeed channels) during automatic landing, from a final approach until a touchdown. It is composed of two key parts: a vision system and an automatic landing system. The first part exploits dedicated image-processing algorithms to identify the number of red and white PAPI lights appearing on an onboard video camera. Its output data—information about an aircraft’s position on a vertical profile of a landing trajectory—is used as one of the crucial inputs to the automatic landing system (the second part), which uses them to control the landing. The control algorithms implemented by the automatic landing system are based on the fuzzy logic expert system and were developed to imitate the pilot’s control actions during landing an aircraft. These two parts were teamed together as a component of a laboratory rig, first as pure software algorithms only, then as real hardware modules with downloaded algorithms. In two test campaigns (software in the loop and hardware in the loop) they controlled an aircraft model in a simulation environment. Selected results, presenting both control efficiency and flight precision, are given in the final section of the paper.

Background. Obstructive sleep apnea (OSA) may predispose patients to acute kidney injury (AKI) and chronic kidney disease (CKD). Objectives. We postulated that apneic episodes during sleep in patients with OSA may result in episodes of subclinical AKI that may be detected by the use of novel sensitive serum and urine markers. The treatment of OSA may protect against renal injury. Material and methods. The study involved 86 men who had positive screening test results for OSA and estimated glomerular filtration rates (eGFR) calculated with the Chronic Kidney Disease Epidemiology Collaboration (CDK-EPI) equation >60 mL/min/1.73 m(2). All the patients underwent overnight polysomnography (the diagnostic night). The patients were divided into 2 groups: 45 patients with mild OSA and 41 patients with moderate-to-severe OSA. Those in the latter group were qualified for 6-8 weeks of continuous positive airway pressure (CPAP) treatment. Blood pressure, serum creatinine, high sensitivity C-reactive protein (h5CRP), urine creatinine, AKI markers cystatin C and neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule 1 (KIM-1), liver-type fatty acid-binding protein, and endothelium marker intercellular adhesion molecule-1 (ICAM-1) were assessed in both groups before and after polysomnography. The sa me parameters were also measured in the patients with moderate-to-severe OSA after CPAP therapy. Results. Kidney injury molecule 1 and urine NGAL significantly increased after the diagnostic night in the whole group and in mild OSA patients (p = 0.04 and p = 0.001, respectively). Serum ICAM-1 significantly decreased after the diagnostic night only in mild OSA patients (p =0.03. Urine cystatin C increased after 6-8 weeks of CPAP treatment in the moderate-to-severe OSA group (0.003). Serum ICAM-1 decreased after the CPAP treatment (p = 0.02). The CPAP therapy led also to a decrease in mean and diastolic (p = 0.005) blood pressure. Conclusions. The pattern of overnight changes in serum and urine AKI markers after apneic episodes during sleep may suggest an increased risk of subclinical AKI in patients with OSA. The CPAP therapy is not protective against AKI, but may reduce some of its risk factors, including high blood pressure and endothelial damage.

Vision-based control in robotics offers versatile automation; however, accessible educational platforms for exploring its integration with AI are still limited. This paper addresses this gap by presenting a small, 3D-printed parallel SCARA robot designed specifically for educational purposes. We...