With the rapid development of artificial intelligence (AI) technology, its application in the field of auditing has gained increasing attention. This paper explores the application of AI technology in audit risk assessment and control (ARAC), aiming to improve audit efficiency and effectiveness. First, the paper introduces the basic concepts of AI technology and its application background in the auditing field. Then, it provides a detailed analysis of the specific applications of AI technology in audit risk assessment and control, including data analysis, risk prediction, automated auditing, continuous monitoring, intelligent decision support, and compliance checks. Finally, the paper discusses the challenges and opportunities of AI technology in audit risk assessment and control, as well as future research directions.

The recession cone and recession function are very important research objects in Convex Analysis. They have extensive applications in the optimization theory. Firstly, we study the properties of the recession cone and recession function. The positive homogeneity and subadditivity of recession function are mainly discussed. And the different methods are considered to prove these properties. Secondly, we discuss the unboundedness of the convex sets and convex functions by using recession cone and recession function.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

Diamond-like Nanocomposites (DLN) is a newly member in amorphous carbon (a:C) family. It consists of two or more interpenetrated atomic scale network structures. The amorphous silicon oxide (a:SiO) is incorporated within diamond-like carbon (DLC) matrix i.e. a:CH and both the network is interpenetrated by Si-C bond. Hence, the internal stress of deposited DLN film decreases remarkably compare to DLC. The diamond-like properties have come due to deform tetrahedral carbon with sp³ configuration and high ratio of sp³ to sp² bond. The DLN has excellent mechanical, electrical, optical and tribological properties. Those properties of DLN could be varied over a wide range by changing deposition parameters, precursor and even post deposition treatment also. The range of properties are: Resistivity 10^-4 to 10¹⁴ Ωcm, hardness 10–22 GPa, coefficient of friction 0.03-0.2, wear factor 0.2-0.4 10^-7mm³/Nm, transmission Vis-far IR, modulus of elasticity 150-200 GPa, residual stress 200-300 Mpa, dielectric constant 3-9 and maximum operating temperature 600^°C in oxygen environment and 1200^°C in O₂ free air. Generally, the PECVD method is used to synthesize the DLN film. The most common procedures used for investigation of structure and composition of DLN films are Raman spectroscopy, Fourier transformed infrared spectroscopy (FTIR), HRTEM, FESEM and X-ray photo electron spectroscopy (XPS). Interest in the coating technology has been expressed by nearly every industrial segment including automotive, aerospace, chemical processing, marine, energy, personal care, office equipment, electronics, biomedical and tool and die or in a single line from data to beer in all segment of life. In this review paper, characterization of diamond-like nanocomposites is discussed and subsequently different application areas are also elaborated.

Recent technological advances in the fields of biomaterials and tissue engineering have spurred interest in biopolymers for various biomedical applications. The advantage of biopolymers is their favorable characteristics for these applications, among which proteins are of particular importance. Proteins are explored widely for 3D bioprinting and tissue engineering applications, wound healing, drug delivery systems, implants, etc., and the proteins mainly available include collagen, gelatin, albumin, zein, etc. Zein is a plant protein abundantly present in corn endosperm, and it is about 80% of total corn protein. It is a highly renewable source, and zein has been reported to be applicable in different industrial applications. Lately, it has gained attention in biomedical applications. This research interest in zein is on account of its biocompatibility, non-toxicity, and certain unique physico-chemical properties. Zein comes under the GRAS category and is considered safe for biomedical applications. The hydrophobic nature of this protein gives it an added advantage and has wider applications in drug delivery. This review focuses on details about zein protein, its properties, and potential applications in biomedical sectors.

This study analyzes the perception of university students regarding the use of virtual reality (VR) in higher education, focusing on their level of knowledge, usage, perceived advantages and disadvantages, as well as their willingness to use this technology in the future. Using a mixed-methods approach that combines questionnaires and semi-structured interviews, both quantitative and qualitative data were collected to provide a comprehensive view of the subject. The results indicate that while students have a basic understanding of VR, its use in the educational context is limited. A considerable number of students recognize VR’s potential to enhance the learning experience, particularly in terms of immersion and engagement. However, significant barriers to adoption were identified, such as technical issues, the high cost of equipment, and inadequate access to technological infrastructure. Additionally, there is a need for broader training for both students and faculty to ensure the effective use of this technology in academic environments. The semi-structured interviews confirmed that perceptions of VR vary depending on prior exposure to the technology and access to resources. Despite the challenges, most students appreciate VR’s potential to enrich learning, although its effective adoption will depend on overcoming the identified barriers. The study concludes that strategies must be implemented to facilitate the integration of VR into higher education, thus optimizing its impact on the teaching-learning process.