The paper evaluated the diagnostic value of laser photoplethysmography when examining patients with chronic lower limb ischemia. A statistical analysis of the research results was made, and diagrams of relationship between the degrees of ischemia and blood flow are presented.

With the development of information technology, electromagnetic radiation becomes a tangible view of the physical (wave) environmental pollution. Modern scientific research aimed at the components of the electromagnetic environment pollution problems mainly involves the anthropocentric approach....

This paper presents a digital model of an intelligent solar-powered street lighting system with integrated energy consumption forecasting, developed in MATLAB/Simulink. The simulation uses real hourly weather data from the Almaty region, where solar irradiance ranged from 0 to 980 W/m² and temperatures varied from –25°C to +35°C. The modeled system includes a 200 W photovoltaic panel, a 120 Ah battery, and LED luminaires up to 60 W. Predictive analysis of the battery’s state of charge (SOC) and need for external power was conducted using AI algorithms ANN, LSTM, GRU, and Random Forest trained on synthetic data from the simulation. Results show the system can operate autonomously for up to 72 hours under adverse weather. The probability of switching to backup power is 27–32% in winter and under 8% in summer. The LSTM and GRU models achieved a mean SOC prediction error of less than 5% versus actual values. The proposed architecture offers a practical and adaptable approach for designing, testing, and optimizing solar-powered lighting in both urban and rural settings across Kazakhstan and similar regions. It demonstrates the potential of combining simulation with AI to support sustainable and resilient outdoor lighting infrastructure.

This paper is devoted to designing, modeling, and analyzing a solar-powered street lighting system using artificial intelligence technologies to predict energy consumption. The system involves the integration of solar panels, batteries, and sensors to efficiently control the brightness of LED lamps depending on the illumination level and the presence of motion in the lighting area. The use of artificial neural networks (LSTM, GRU, Random Forest) provided accurate prediction of solar energy generation and the need to connect to the city power grid during periods of low solar activity. The developed model was implemented in MATLAB Simulink, considering actual weather data. The results showed that the system can operate autonomously for up to three days under unfavorable weather conditions, reducing power by 30%. The need for connection to the external network is no more than 10% in summer and up to 30% in winter. The prototype will be implemented in Kazakhstan to validate the model and further optimize its operation.

End-fire multibeam radial line slot array antennas

Given article illustrates that the digitalization of the maritime industry improved the connection between the various maritime stakeholders and at the same time opened the maritime industry for the risks and vast consequences of cyber-attacks. This research paper shows the consequences of such cyber attacks to the whole operation of the maritime industry. This investigation paper described various types of consequences that can lead to the breakdown of whole operations in the maritime industry. The written research paper gives some examples regarding the cybersecurity cases in order to show the importance of this aspect for the future development of this sphere.