Startup accelerators are a highly useful part of the entrepreneurial ecosystem. They are responsible for supporting young innovative enterprises with innovative ideas at the early stages of their development. Problems related to building a business model, raising funds for business development, or determining the directions of development of the products and services offered are often just the tip of the iceberg, which can be a serious obstacle preventing survival on the market and achieving commercial success. Accelerators are entities supporting innovation, which, using the tools and programs they have, can significantly facilitate issues related to running a business by immature start-ups and significantly contribute to overcoming the challenges that constantly appear before them. Due to the importance of innovation in the global economy and its obvious connection with start-ups, scientists in the last decade have clearly marked their interest in the subject of start-up accelerators. The purpose of this research work is to present the current state of knowledge in the area of accelerators and to systematize it. For this purpose, a literature review describing issues related to start-up accelerators was reviewed and a bibliometric analysis was carried out. As a result of the research, the topics in the area of accelerators that were most often taken up by scientists and the details on which previous publications focused were shown. The authors hope that the presented study will be valuable material for theoreticians conducting future research on start-up accelerators, and will also be a useful support for practitioners from such entities as start-ups, accelerators, corporations, and government agencies.

Finishing operations are one of the most challenging tasks during a manufacturing process, and are responsible for achieving dimensional accuracy of the manufactured parts and the desired surface topography properties. One of the most advanced finishing technologies is grinding. However, typical grinding processes have limitations in the acquired surface topography properties, especially in finishing difficult to cut materials such as Inconel 625. To overcome this limitation, a new type of grinding wheel is proposed. The tool is made up of grains of different sizes, which results in less damage to the work surface and an enhancement in the manufacturing process. In this article, the results of an experimental study of the surface grinding process of Inconel 625 with single-granular and multi-granular wheels are presented. The influence of various input parameters on the roughness parameter (Sa) and surface topography was investigated. Statistical models of the grinding process were developed based on our research. Studies showed that with an increase in the cutting speed, the surface roughness values of the machined samples decreased (Sa = 0.9 μm for a Vc of 33 m/s for a multigranular wheel). Observation of the grinding process showed an unfavorable effect of a low grinding wheel speed on the machined surface. For both conventional and multigranular wheels, the highest value for the Sa parameter was obtained for Vc = 13 m/s. Regarding the surface topography, the observed surfaces did not show defects over large areas in the cases of both wheels. However, a smaller portion of single traces of active abrasive grains was observed in the case of the multi-granular wheel, indicating that this tool performs better finishing operations.

Additive manufacturing has garnered significant interest in various industries due to its flexibility and capability to produce parts with complex shapes. However, issues related to surface quality, such as roughness and microstructural defects, necessitate the use of post-processing techniques to achieve the desired properties. Ti6Al4V alloy, produced additively, was finished using low-energy discharges, and the new surface integrity properties resulting from the induced heat energy were investigated. To further understand the influence of discharge energy on the formation of the new layer, roughness parameters and power spectral density were used to characterize the surface topography. SEM and EDS analyses were performed to examine the morphology and microstructural defects such as microcracks. The results indicate that the heat energy induced by the discharge improved the properties of the surface. SEM analysis revealed that the new layer was characterized by a reduction in defects such as unmelted particles, the balling effect, and microcracks. At the lowest investigated discharge energy of E = 0.21 mJ, surface roughness, Sa, was reduced by about 69%, which is equal to about 2 μm, accompanied by a significant decrease in microcracks. EDS analysis indicated that the diffusion of copper and zinc from the electrode to the top surface was related to the discharge energy. Furthermore, prediction models of the influence of wire electrical discharge polishing parameters, including discharge energy, wire speed, and time interval, on the surface roughness and material removal rate (MRR) were developed using the response surface methodology.

The article addresses the problem of the insufficient empirical recognition of the determinants of trust in artificial intelligence (AI) algorithms in organizations operating under conditions of sustainable development. The aim of the study was to identify the factors shaping organizational trust in AI and to examine how perceived trustworthiness, transparency, and effectiveness of algorithms influence their acceptance in the work environment. The research was conducted using a quantitative survey-based approach among organizational employees, which enabled the analysis of relationships between key variables and the identification of factors that strengthen or limit trust. The results indicate that algorithmic transparency, the reliability of generated outcomes, and the perceived effectiveness of AI applications significantly foster trust, whereas concerns related to errors and the decision-making autonomy of systems constitute important barriers to acceptance. Based on the findings, a conceptual and exploratory model of trust in AI was proposed, which may be used to diagnose the level of technology acceptance and to support the responsible implementation of artificial intelligence-based solutions in organizations. The contribution of the article lies in integrating organizational and technological perspectives and in providing an empirical approach to trust in AI within the context of sustainable development.

Grinding is one of the basic finishing operations, which allows high dimensional accuracy of the workpiece. It has a strong impact on the properties of the Grinding is one of the basic finishing operations, which allows high dimensional accuracy of the workpiece. It has a strong impact on the properties of the