European Journal of Science, Innovation and Technology

Adapting Code Review Processes to the Conditions of AI-Assisted Software Development

Yurii Bezhentsev — Wed, 06 May 2026 00:00:00 +0300

The article presents an analysis of the transformation of code review processes in the context of software development with the use of artificial intelligence. The study is conducted in the format of a systematic review and analytical synthesis of academic publications focusing on code generation, development productivity, and the organization of change validation processes. The primary focus is on the relationship between the speed of code creation, the characteristics of introduced changes, and the ability of the review process to ensure their reliable interpretation and safe integration. The key parameters determining the effectiveness of code review are examined, including temporal characteristics, the structure of changes, and cognitive load. It is established that the impact of code generation tools is indirect and manifests through the formation of asymmetry between the intensity of generation and the capacity for review. It is shown that even with improvements in the quality of automatically generated code, the risk of uncritical acceptance and the integration of hidden logical inconsistencies remains. An original adaptive code review model is proposed, reflecting a transition from single-stage review to a multi-level system that includes preliminary filtering, structured analysis, risk assessment, and a feedback loop. The results obtained allow code review to be considered as a controllable risk regulation mechanism determining the stability and predictability of the development process. The practical significance of the study lies in substantiating the need to structure code review processes, limit the scope of changes, and increase transparency in the origin of code fragments. The article will be useful for software developers, engineering managers, and specialists in software process management.

Molecular Detection and Statistical Association of Carbapenem Resistance Determinants (blaOXA and blaNDM) in Clinical Isolates of Escherichia coli and Klebsiella pneumoniae from Southeastern Nigeria

Mon, 11 May 2026 21:16:01 +0300

Background: Carbapenem-resistant Enterobacteriaceae (CRE) represent a critical public health threat, with limited epidemiological data from southeastern Nigeria. This study investigated the prevalence of carbapenem resistance and the distribution of blaOXA and blaNDM genes among clinical isolates of Escherichia coli and Klebsiella pneumoniae from a tertiary hospital in Enugu, Enugu State.

Methods: A total of 210 non-duplicate urine samples were collected from patients attending Enugu State University Teaching Hospital (ESUTH). Bacterial isolates were identified using standard microbiological techniques and API 20E system. Antimicrobial susceptibility testing was performed by disk diffusion method, with carbapenem resistance phenotypically confirmed using the Modified Hodge Test. Molecular detection of blaOXA and blaNDM genes was conducted using conventional PCR. Statistical associations between resistance phenotypes and demographic variables were analyzed using SPSS version 25.

Results: Gram-negative bacteria were isolated from 151 (71.9%) samples, comprising 89 (42.4%) E. coli and 62 (29.5%) K. pneumoniae. Phenotypic carbapenem resistance was detected in 24 (15.9%) isolates: 10 (11.2%) E. coli and 14 (22.6%) K. pneumoniae. All carbapenem-resistant isolates exhibited multidrug resistance phenotypes. Molecular analysis revealed that 21 (87.5%) of phenotypically resistant isolates harbored carbapenemase genes: blaNDM was detected in 12 (50.0%) isolates, blaOXA in 5 (20.8%), and co-occurrence of both genes in 4 (16.7%). K. pneumoniae demonstrated significantly higher gene carriage (92.9%) compared to E. coli (80.0%). Statistical analysis showed significant association between carbapenem resistance and patient age >40 years (p=0.023), but not with gender (p=0.412).

Conclusion: This study documents a high prevalence of blaNDM and blaOXA genes among CRE isolates in southeastern Nigeria, with K. pneumoniae serving as a major resistance reservoir. The findings underscore the urgent need for enhanced surveillance, antimicrobial stewardship, and infection control measures in the region.

Factors Influencing Green Logistics Adoption Intentions among Small and Medium Enterprises (SMEs) in Vietnam: An Empirical Study Based on the TOE Framework

Nguyen Thi Thanh Hai — Tue, 12 May 2026 00:00:00 +0300

In an era of global environmental volatility, transitioning to sustainable practices has become a strategic imperative for Small and Medium Enterprises (SMEs) within the global value chain. This study investigates the factors influencing green logistics adoption intentions among SMEs in Vietnam by integrating the Technology-Organization-Environment (TOE) framework. Data were collected through a quantitative survey of 367 managers and owners of Vietnamese SMEs and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. The empirical results indicate that all seven proposed hypotheses are supported. Notably, top management support and regulatory pressure emerged as the most significant predictors of adoption intention. Furthermore, while relative advantage and compatibility positively influence adoption, technological complexity remains a critical barrier. Market pressure and the quality of green human resources also play vital roles in driving the green transition. Theoretically, this research extends the applicability of the TOE framework to the SME context in an emerging market. Practically, the findings offer evidence-based insights for policymakers to design targeted support mechanisms and for SME managers to strategically align their operations with international environmental standards.