With the increasing demand for sustainable energy, advanced characterization methods are becoming more and more important in the field of energy materials research. With the help of X-ray imaging technology, we can obtain the morphology, structure and stress change information of energy materials in real time from two-dimensional and three-dimensional perspectives. In addition, with the help of high penetration X-ray and high brightness synchrotron radiation source, in-situ experiments are designed to obtain the qualitative and quantitative change information of samples during the charge and discharge process. In this paper, X-ray imaging technology based on synchrotron and its related applications are reviewed. The applications of several main X-ray imaging technologies in the field of energy materials, including X-ray projection imaging, transmission X-ray microscopy, scanning transmission X-ray microscopy, X-ray fluorescence microscopy and coherent diffraction imaging, are discussed. The application prospects and development directions of X-ray imaging in the future are prospected.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.

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.

Employee retention is a critical concern for organizations in today’s dynamic labor market. This paper introduces a novel framework, integrating “absolute potential of the employee” and “risk associated with leaving the employee”, to address this challenge. Findings from the study suggest that this framework can effectively assist organizations in strategizing retention techniques. The research methodology employed an exploratory research design and collected data from 576 employees across various sectors. The results indicate significant implications for organizational risk assessment and employee retention strategies.

In the current work, it was investigated to the K X-ray fluorescence efficiency and chemical effect on vacancy transfer probability for some tin compounds. We used Br₂Tin, TinI₂, SeTin, TinF₂, TinSO₄, TinCl₂, TinO and TinS compounds for experimental study. The target samples were irradiated with ²⁴¹Am annular radioactive source at the intensity of 5 Ci which emits gamma rays at wavelength of 0.2028 nm. The characteristic x-rays emitted because of the excitation are collected by a high-resolution HPGe semiconductor detector. It has been determined that the experimental calculations of the tin (Sn) element are compatible with the theoretical calculation. In addition, we have calculated the experimental intensity ratios, fluorescence yields and total vacancy transfer probabilitiesfor other Sn compounds.