With the development of technology, the need for personalized medicine has increased day by day. There are also growing concerns about harmful substances in the environment. Therefore, it is crucial to monitor and detect the specific target in the environment and biological systems in real time and accurately. Chemical sensors have shown wide application prospects as highly sensitive and selective detection tools. This article systematically compares the similarities and differences of various recognition methods in terms of recognition mechanism, sensitivity, and selectivity, and deeply explores the diversity and applicability of signal transduction methods from optical to electrical signals. Overall, these methods have their advantages, and in specific applications, the optimal solution needs to be selected in combination with the characteristics of the target. Moreover, this paper also briefly discussed methods that transform the recognition signals into electrochemical and optical signals. Future research should apply more small-molecule-specific recognition methods to the recognition of larger molecules, finding more specific molecules and universal synthetic methods.

This paper highlights developments in microbial electrosynthesis (MES), metabolic engineering, and photosynthetic biohybrid systems (PBSs) for biofuel production, which offer a sustainable solution to lessen dependency on fossil fuels and the emission of greenhouse gases. MES uses electroactive microbes to convert CO2 into ethanol, methane, and other fuels using renewable electricity while integrating wastewater treatment; metabolic engineering improves CO2 fixation by redesigning microbial pathways; and PBSs combine inorganic semiconductors with biological catalysts to improve solar energy conversion. Methane synthesis through hydrogenotrophic methanogenesis and ethanol production via acetyl-CoA pathways are examples of targeted biofuel synthesis. However, the overall energy yields remain suboptimal for large-scale deployment. Slow reaction rates, expensive hydrogen, and fluctuating CO2 fixation efficiencies in microalgae systems are among the difficulties that are impacted by reactor design and operating factors. Process optimization and strain engineering innovations hold promise for scalability. However, further research is required due to the infrastructural requirements and economic viability of CO2 capture and hydrogen delivery. Realizing the full potential of microbial CO2 conversion technologies in reaching carbon neutrality will require addressing these technological and financial obstacles through interdisciplinary methods.

Particle Image Velocimetry (PIV) method is used to measure the flow through a prototype mixing grid for nuclear reactor. In this preliminary experiment, there are no fuel rods, the grid is empty. We observe the pattern of jets and wakes, which is deformed by the transient flow introduced by the mixing vanes. The flow displays relatively low dependence on Reynolds number and high dependence on the downstream distance. In the contribution, there are shown the spatial maps of mean velocity, turbulence intensity and turbulence flatness.

In order to ensure the optimal level of occupational health and safety, a whole series of technical measures are taken for underground activities. However, in accidental situations, generated by ignoring dangerous situations or violating occupational health and safety regulations, explosion-type phenomena occur with extremely severe repercussions in terms of loss of human lives, destruction of electromechanical equipment, as well as temporary immobilization or total loss of coal reserves. The effect of an underground explosion affects the main ventilation station in relation to the distance from the explosion site, these effects can be non-destructive or destructive. This article presents a simulation of a low-intensity explosion (2 bars) in the ventilation network of the Lupeni mine, with the aim of identifying critical areas and proposing safety measures. Using the specialized ventilation network modeling and solving program - Ventsim Visual Design, the simulation highlights the propagation of the shock wave within the galleries and identifies vulnerable points. The paper provides a detailed analysis of the effects of the explosion on the general ventilation, as well as recommendations for improving the ventilation infrastructure. In paper will present the results obtained from the simulation of a small intensity explosion phenomenon (2 bars) on the ventilation network of the Lupeni mine.

The application of Industry 4.0 and advanced controllers is advancing rapidly in deep drawing and stamping companies. The main goals of process monitoring, sensor data analysis, and the design of new controllers are process optimization and increased process robustness. These approaches directly result in reduced scrap and the development of more environmentally friendly processes. During process monitoring, measuring draw-in is crucial for both the try-out of new tools and production monitoring of stamping operations. This measurement allows for adjustments in lubrication and blank-holder forces, leading to a more robust process. This paper presents a novel method for the in-line draw-in measurement using cost-effective and robust tactile sensors based on pneumatic cylinders. The new sensor can track draw-in when curved blank-holders are used, allowing the monitoring of the full draw-in temporal curve. This paper first presents the design of the new sensor along with its accuracy measurements. Next, the sensor is tested using curved blank holders, and the buckling behaviour of the contacting finger is analysed. Finally, the sensor’s performance in a real-world environment is evaluated.

Over the last 4 years, an empirical model describing the current from galvanic anodes has been released based on limited data from some galvanic anodes. The model describes how the current from these anodes appears to halve over set time intervals. This ‘ageing constant’ has been used to design anode systems based on a minimum current requirement for protection and broadly applied to other galvanic anode systems. This is a radical change from the responsive behaviour model of corrosion management typically applied to galvanic anodes where the effect of the anodes was more typically tested using methods such as visual inspection, steel potentials and steel corrosion rates. In this work, we will break down the hypotheses behind this model; from the minimum current threshold being the same for all galvanic anode systems, ignoring the current spread from different anode placements, and the predictive power of this model, using data from a system cited by these authors from a Concrete Preservation Technologies Ltd (CPT) hybrid anode system. The authors of the half-life model utilised the first 7 years of data to generate an ageing constant. Now, with over 17 years of data, the model will be assessed and dramatically different conclusions drawn on the effectiveness of this model for predicting the life of CPT anodes.

Millions of people globally experience visual impairment, severely limiting safe and independent mobility. This paper presents the design, development, and validation of an AI-enabled smart cane integrating ultrasonic and vision-based sensing for obstacle detection and object recognition. The system combines four HC-SR04 ultrasonic sensors with a camera connected to a Raspberry Pi 4B, running a custom-trained YOLOv4-tiny convolutional neural network (CNN) model to identify key navigational features such as doors, stairs, and ramps. The Arduino Mega handles low-latency ultrasonic sensing and vibration feedback, while the Pi processes visual frames and provides audio cues using an offline text-to-speech engine. In trials, the ultrasonic module achieved near-perfect obstacle detection within 1.2 m, and the vision system correctly identified trained objects under standard lighting, though accuracy declined under strong glare. Despite hardware limitations, the system effectively fuses both sensing modes to alert users via haptic and voice feedback. The paper evaluates all subsystems individually, verifying sensor accuracy, object detection reliability, and thermal performance under continuous load. This research contributes a portable, affordable solution toward safer navigation for the visually impaired using real-time embedded AI.

The development of sustainable, high-performance cementitious materials for infrastructure rehabilitation presents not only technical but also institutional and regulatory challenges. Belitic calcium sulfoaluminate (BCSA) cement—first developed in the United States in the 1970s—has emerged as a promising low-carbon alternative, especially in applications requiring rapid strength gain. This presentation reviews recent progress in BCSA cement technology, examines some of its performance characteristics and environmental benefits, and explores its synergistic potential as an early-strength enhancer in widely adopted low-carbon cements such as Portland-limestone cement (PLC) and limestone-calcined clay cement (LC3.

Additive manufacturing (AM) is a layer-by-layer process, of joining powder material to build solid parts from 3D model data. Titanium powders are very reactive when exposed to ambient conditions, which can result in degradation of the powder. Therefore, correct powder handling and storage play a crucial role in ensuring the required performance and part quality. This paper presents an Internet of Things (IoT)-based system designed to monitor temperature and humidity in real time, enabling detection, notification and data recording. The development of the monitoring system was accomplished based on the environmental data received during handling and storage of titanium powder from the Centre for Rapid Prototyping and Manufacturing (CRPM). The system uses four DHT22 sensors, where data is displayed on an organic light-emitting diode (OLED) screen and graphically analysed via the IoT-based ThingSpeak web platform. When the conditions exceeded the threshold, the automation tool IFTTT (If This Then That) automatically sent a notification to the user via email for further action. Temperature and humidity fluctuations were recorded and compared using graphical representations analysed from ThingSpeak and MATLAB. The system effectively detected minor environmental changes and demonstrated reliable performance in maintaining controlled conditions during powder handling and storage processes.

As a clean and renewable energy source, hydropower occupies an important position in China's energy transition. This paper systematizes the technical principles, development status, advantages, and challenges of hydropower and looks forward to its prospects. The study points out that China is rich in hydropower resources and has sufficient technological reserves, but the development rate is low and needs to be upgraded urgently. Currently, hydropower development is facing problems such as institutional monopoly, thermal power competition, and ecological conflicts, which need to be solved through power market reform, optimization of scheduling mechanisms, and promotion of integrated development of river basins. At present, China's hydropower installed capacity continues to grow, with high- power units and intelligent technology to promote the upgrading of the industry, but we need to pay attention to the ecological impact and the challenge of uneven regional resources. In the future, the construction of hydropower bases in the west and the layout of pumped storage power plants will become a key focus, helping to realize the goal of carbon neutrality. This paper emphasizes that hydropower has economic, social, and environmental benefits, and its sustainable development needs to be driven by both policy support and technological innovation.