The cross wire projection welding of wires (Al 5182, = 4 mm) performed using the conventional (i.e. pneumatic) electrode force system was subjected to thorough numerical analysis. Calculations were performed until one of adopted boundary conditions, i.e., maximum welding time, maximum penetration of wires, the occurrence of expulsion or the exceeding of the temperature limit in the contact between the electrode and the welded material was obtained. It was observed that the ring weld was formed within the entire range of welding parameters. The process of welding was subjected to optimisation through the application of a new electromechanical electrode force system and the use of a special hybrid algorithm of electrode force and/or displacement control. Comparative numerical calculations were performed (using SORPAS software) for both electrode force systems. Technological welding tests were performed using inverter welding machines (1 kHz) provided with various electrode force systems. The research also involved the performance of metallographic and strength (peeling) tests as well as measurements of welding process characteristic parameters (welding current and voltage).
The welding process optimisation involving the use of the electromechanical force system and the application of the hybrid algorithm of force control resulted in i) more favourable space distribution of welding power, ii) energy concentration in the central zone of the weld, iii) favourable (desired) melting of the material within the entire weld transcrystallisation zone and iv) obtainment of a full weld nugget.

The rapid development of cities and urbanization in China has forced the growth of new channels for buying agricultural products. The purpose of this research is to examine how Internet of Things (IoT’s) technologies can digitize a traditional fresh food supply chain. Comparative and descriptive analysis methods are used to highlight the major pain points in the traditional supply chains and assess how digital transformation could help. We delve into every part of digital transformation, which includes establishing an information platform based on IoT and developing smart storage options. Our findings revealed that through end-to-end digital integration, supply chain efficiency is improved with shorter lead times and leaner inventories that yield reduced costs as well as fewer losses while ensuring product quality and traceability. In sum, such an approach would enhance sustainability within the fresh food value chain. As such, our article highlights key aspects of transitioning towards a digital environment in this sector for those planning similar ventures.

Abrupt changes in environmental temperature, wind and humidity can lead to great threats to human life safety. The Gansu marathon disaster of China highlights the importance of early warning of hypothermia from extremely low apparent temperature (AT). Here a deep convolutional neural network model together with a statistical downscaling framework is developed to forecast environmental factors for 1 to 12 h in advance to evaluate the effectiveness of deep learning for AT prediction at 1 km resolution. The experiments use data for temperature, wind speed and relative humidity in ERA-5 and the results show that the developed deep learning model can predict the upcoming extreme low temperature AT event in the Gansu marathon region several hours in advance with better accuracy than climatological and persistence forecasting methods. The hypothermia time estimated by the deep learning method with a heat loss model agrees well with the observed estimation at 3-hour lead. Therefore, the developed deep learning forecasting method is effective for short-term AT prediction and hypothermia warnings at local areas.

The problem of the synthesis of new type nanomaterials in the form of nano-coatings with sub-nanometric heterogeneity has been formulated. It has been presented an analysis of influences of physical vapor deposition in ultrahigh vacuum on the process of intermixing a film with a substrate, including the results, which has been obtained under the formation of transition metal – silicon interface. The generalization of the obtained experimental results develops an approach to the development of new nano-coatings with low-dimensional heterogeneity. The principles of constructing such low-dimensional nano-coatings, their properties and possible applications are considered. 

Plum (Prunus domestica) is a seasonal nutraceutical fruit rich in many functional food nutrients such as vitamin C, antioxidants, total phenolic content, and minerals. Recently, researchers have focused on improvised technologies for the retention of bioactive compounds during the processing of perishable fruits; plum is one of these fruits. This study looked at how the percentage of moisture content and percentage of acidity were affected by conventional drying and osmotic dehydration. Total phenolic content (mg GA/100 g of plum), total anthocyanin content (mg/100 g), and vitamin C (mg/100 g) Conventional drying of fruit was carried out at 80.0 ℃ for 5 h. At various temperatures (45.0 ℃, 50.0 ℃, and 55.0 ℃) and hypertonic solution concentrations (65.0 B, 70.0 B, and 75.0 B), the whole fruit was osmotically dehydrated. It was observed that the osmotically treated fruit retains more nutrients than conventionally dried fruit. The total phenolic content of fruit significantly increased with the increase in process temperature. However, vitamin C and total anthocyanin content of the fruit decreased significantly with process temperature, and hypertonic solution concentration was observed. Hence, it was concluded that osmodehydration could be employed for nutrient retention in plum fruit over conventional drying. This process needs to be further refined, improvised, and optimised for plum processing.