European Journal of Science, Innovation and Technology

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

2026-05-06T10:07:17+03:00

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

2026-05-11T21:16:01+03:00

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

2026-05-12T10:36:26+03:00

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.

Diffusion and Adsorption Characteristics of Crude Oil-Contaminated Silty Clay Soil Stabilised with Freshwater Limpet Shell Ash and Cement Combination

2026-05-13T20:04:19+03:00

The diffusion of Total Petroleum Hydrocarbon (TPH) pollutants to groundwater at crude oil-contaminated sites in Nigeria's Niger Delta is a problem that severely affects drinking water. But the inclusion of cementitious materials will reduce the diffusion rate to groundwater. This study analyses the Effective Diffusion Coefficient (EDC)/Tortuosity Factor (TF) and Retardation Factor (Rd) of Crude Oil-Contaminated Soils (COCS) stabilised with Freshwater limpet shell ash and cement combination (FWLSA-C). Uncontaminated soils were sampled at a depth of 1.0 m and mixed with 0, 2, 5, 10, 15 and 20% of crude oil by weight to produce artificially contaminated soils. Freshwater limpet shells were sourced from the Esaman River, Delta State, calcined to ash at 887°C for four hours and ground to powder. The ash oxide content was determined with X-ray fluorescence. The soil samples were mixed with different amounts of cement and ash. The combinations were: 0% cement and 0% ash, 5% cement with 2% ash, 5% cement with 3% ash, 5% cement with 5% ash, 5% cement with 10% ash, 5% cement with 15% ash, and 5% cement with 20% ash. The EDC/TF and Rd were determined using standard methods. The EDC/TF and Rd for 0% COCS without FWLSA-C were 0.00 m²/s/0.00 and 0.00; 20% COCS without FWLSA-C were 2.06E-10 m²/s/7.09E-02 and 11.64; and the average of 9.31E-11 m²/s/6.92E-02 and 28.49 by adding the FWLSA-C. The FWLSA-C reduced the EDC/TF from 2.06E-10 to 3.50E-11 m²/s/7.09E-02 to 6.66E-02 and increased Rd from 11.64 to 40.16, respectively. Therefore, this study revealed that freshwater limpet shell ash and cement combination (FWLSA-C) will slow the diffusion rate of Total Petroleum Hydrocarbon (TPH) contaminants to groundwater in crude oil-contaminated sites within the Niger Delta in Nigeria.

Data-Driven Assessment of Low-Speed Wind Energy Harvesting Potential Using MATLAB/Simulink Modeling

2026-05-13T20:18:09+03:00

This study presents a data-driven evaluation of a wind energy harvesting system designed for low power applications, particularly wireless sensor networks (WSNs). High resolution wind speed data were collected over a one-year period from January-December 2025 at the Federal University of Petroleum Resources, Effurun (FUPRE), Nigeria, using a calibrated Automated Weather Observing Station (AWOS). A comprehensive system model was developed in MATLAB/Simulink, incorporating aerodynamic wind turbine dynamics, electromagnetic energy conversion, rectification, DC-DC conversion, maximum power point tracking (MPPT) using the perturb and observe (P&O) algorithm, and a power management system (PMS) with battery storage. Simulation results reveal strong seasonal variations in harvested power, with peak performance observed in March, where average DC-DC output reaches approximately 38.022 mW and daily harvested energy peaks at about 0.766 Wh/day. Lower performance is recorded during periods of reduced wind activity, particularly between October and November. Despite these fluctuations, the PMS effectively regulates power flow, ensuring stable energy delivery to the load. The system demonstrates a relatively constant efficiency of approximately 16.47% across all months, indicating stable internal conversion performance. Overall, the results confirm the feasibility of utilizing low-speed wind energy for continuous power supply in autonomous systems. The study highlights the effectiveness of integrating real environmental data with intelligent power management strategies to enhance reliability and energy utilization in wind energy harvesting applications.