This paper investigates the application of micro:bit-based S2 robotic set within an extracurricular STEM club at an evening junior high school in Greece. The club aimed to engage students in activities that would foster their connection to the school community while simultaneously enhancing their education in Science, Technology, Engineering, and Mathematics. The members of the club, both adults and minors, used the micro:bit and the kit’s peripheral devices in small projects. At the end of the year, they created puzzles using the micro:bit for an environmental escape room. The methodology involved a qualitative case study, based on observations and student feedback collected throughout the school year. Findings indicate that this specific educational robotic set can be effectively utilized in an evening school setting to increase student motivation and collaboration, improve problem-solving abilities, and enhance the understanding of abstract concepts. Simultaneously, challenges emerged related to students’ limited available time, technological limitations of the set, and the persistent need for specialized teacher training.

This paper proposes the application of Particle Swarm Optimization (PSO) technique to tune Power System Stabilizers (PSS) for damping small signal oscillations in the high-voltage transmission network of the Western Region of Saudi Arabia. The system has six thermal generating stations and works at 380 kV, 230 kV, and 132 kV transmission voltage levels. The excitation systems are of IEEE type 1. This iterative process aims to fine tune the parameters of controllers to achieve the desired damping for the targeted oscillation modes. The preliminary investigations indicate that the system damping against three-phase short circuits is significantly better with PSO tuned PSS when compared to the conventional PSS.

Supply Chain 4.0 represents a transformative shift in the way businesses manage and optimize their supply chains. Powered by technologies such as blockchain, cloud analytics and advance Security solutions will change the way that businesses manage and optimize their supply chain. The key objective of this transformation is to have efficient, transparent and agile supply processes, which can adapt quickly to dynamic market conditions. With blockchain technology, supply chain partners can achieve a high level of trust and transparency, as it enables secure, decentralized, and immutable record-keeping. With the help of cloud-based analytics, it becomes easy to collect, process and visualize the data in real time which leads to predictive analytics, enhanced decision making and increased operational efficiency. Simultaneously, strong security solutions are essential to safeguard confidential asset data and cyberattacks to ensure supply chain reliability and quality. By combining the two, supply chain stakeholders can achieve real-time innovation with the ability to drive seamless start-to-finish visibility, rapid decision-making, and a resilient supply chain. I outline how a handful of digitized supply chain elements are interconnected and work together as Supply Chain 4.0 to further deliver supply chain innovation and competitiveness in the global supply network in the future.

The focus of this work is the development of two types of low-cost photoacoustic (PA) CO2 sensors, the first was made from mid-infrared (mid-IR) light emitting diode (LED) and the second was made from micro-electro-mechanical system (MEMS) hotplate. Both sensors use MEMS microphones for the detection of the generated acoustic signal. These sensors have advantages of low power consumption, small size and low cost. Analyses of results from both sensors show that temperature change (within−20°C–50°C range) affects their signal amplitude and sensitivities. Results also show that the absence of buffer gas in the cell reduces the PA signal amplitude. Furthermore, comparison of results from the sensors indicate that the LED sensor is more sensitive by about one order of magnitude while the hotplate sensor, which is less expensive, has a better noise performance. This is the first time that such comparison is done and it is important because it reveals the advantages and limitations of these sensors. The findings is vital for determining which sensor will be suitable for certain applications, considering the cost.

The development of an ecosystem that balances consumer convenience and security is imperative given the expanding market for electric vehicles (EVs). The vast amount of data that EV charging station management systems (EVCSMSs) give is powered by the Internet of Things (IoT) ecosystem. Intrusion Detection Systems (IDSs), which track network traffic to spot potentially dangerous data exchanges in IT and IoT contexts, are constantly improving in terms of efficacy and accuracy. Intrusion detection is becoming a major topic in academia because of the acceleration of IDS development caused by machine learning and deep learning techniques. The goal of the research presented in this paper is to use a machine-learning-based intrusion detection system with low false-positive rates and high accuracy to safeguard the ecosystem of EV charging stations (EVCS).

Lead telluride (PbTe) stands out as a significant thermoelectric material suitable for use in the intermediate temperature range. Nonetheless, the thermoelectric performance of n-type PbTe is constrained by its low figure of merit (zT). This investigation reveals a notable enhancement in the thermoelectric characteristics of PbTe alloys through strategic co-doping with trace amounts of bismuth (Bi) and iodine (I). The Pb1−xBixTe1−xIx alloys (x= 0.00%, 0.05%, 0.10%, 0.20%, and 0.50%) are synthesized through a systematic stepwise method. The incorporation of Bismuth and Iodine leads to an increase in carrier concentration while simultaneously lowering lattice thermal conductivity, attributed to heightened phonon scattering at grain boundaries and point defects. The maximum zT of 0.9 is attained at 725 K for the 0.20% co-doped sample, whereas the 0.05% co-doped sample shows the highest average zT (∼0.7) within the 323 K–723 K interval. The results indicate a direction for enhancing the thermoelectric efficiency of PbTe alloys, especially in n-type materials.

Throughout history, solar energy has been widely utilized in conventional technologies, especially when alternative energy sources are unavailable. As awareness of environmental costs grows and alternatives like gasoline face limitations, solar energy has gained broader adoption. Solar tracking devices are considered highly successful in enhancing the efficiency of solar panels by precisely tracking the sun’s trajectory. These devices enhance solar panel alignment, augmenting energy output by ensuring constant sunlight exposure. Solar energy entails the conversion of sunlight into thermal or electrical energy. The United States, one of the globe’s most affluent solar resources, utilizes solar power as one of the cleanest and most plentiful renewable energy sources.

It is the design criteria of driving LEDs at constant current and keeping the input current’s harmonics low, attaining a high power factor, and maximizing efficiency. For low power general purpose lighting buck converter can be chosen for simplicity and reduced cost. It is a difficult to improve power quality parameter like, the THD (total harmonic distortion) and power factor of ac mains. In the proposed topology, the operation for high power factor and low THD at the AC mains’ input is accomplished through buck converter operation in both discontinuous conduction mode (DCM) and continuous conduction mode (CCM) with a suitable control circuit. This paper assures constant current in both cases for suitable design of control circuit. Over voltage protection has been incorporated. To validate the LED driver circuit, simulation studies are carried out.

The creeping flow of an incompressible, bounded micropolar fluid past a porous shell is investigated. The porous shell is modeled using a Darcy equation, sandwiched between a pair of transition Brinkman regions. Analytical expressions for the stream function, pressure, and microrotations are given for each region. Streamline patterns are presented for variations in hydraulic resistivity, micropolar constants, porous layer thickness, and Ochoa-Tapia stress jump coefficient. An expression for the dimensionless drag for the unbounded case of the system is presented, and its variation with hydraulic resistivity and porous shell thickness is presented. The unbounded case represents a theoretical model for oral drug delivery using porous microspheres. It was found that optimal circulation between the porous region and the outer fluid occurred for low values of hydraulic resistivity and for a complete porous sphere.

In this study, a method to evaluate the electro-magnetic damping effect produced by the movement of a permanent magnet inside of a conductive pipe, is proposed. Neither the residual flux density of the magnet, nor the electric conductivity of the pipe is required, but instead, only the magnet height, the pipe length, and the falling time of the magnet inside the tube, are necessary to compute the damping coefficient. Accordingly, cylindrical neodymium magnets of close residual flux densities, but various diameters and heights, are tested against copper pipes of various thicknesses. Using the falling time measured for each magnet-pipe combination, the corresponding damping coefficient is computed, and the influence of various geometrical parameters on the damping coefficient is clarified. Clearance between the magnet and pipe is identified as essential to describe this damping phenomenon.