Kabarak University

The advent of quantum computing presents a formidable threat to the security of digital information, particularly for the e-commerce sector, which relies heavily on cryptographic protocols for secure transactions and data protection. This systematic literature review examines the transition from current cryptographic standards to post-quantum cryptography (PQC) within e-commerce security frameworks. The study addresses the urgent need for quantum-resistant algorithms to safeguard against the looming "Q-Day," when quantum computers will be capable of breaking widely used public-key encryption schemes. Through a systematic review of peer-reviewed literature, this paper synthesizes existing research on the vulnerabilities of current e-commerce security, the development and standardization of PQC algorithms, and the strategic roadmaps for their implementation. Our findings reveal a consensus on the theoretical robustness of PQC candidates, such as lattice-based, code-based, and hash-based cryptography. However, significant challenges remain in the practical integration of these algorithms into legacy e-commerce systems, including performance overhead and the need for crypto-agility. The review highlights the critical role of standardization bodies like NIST in guiding the transition and the necessity for proactive, phased adoption by online businesses. This paper concludes by discussing the implications for the e-commerce industry and outlining a research agenda focused on developing and implementing practical, efficient, and secure quantum-resistant security frameworks for the post-quantum era.

A Kenyan humid savanna in Lambwe Valley is dominated by trees of the genus Acacia and Combretum. The ecosystem is subjected to livestock grazing at varied intensities and fluctuating rainfall amounts. Notable increase in livestock densities and declining rainfall amounts are raising concerns regarding the sustainability of the humid savanna. Sap flow measurements in mature representative trees of A. ancystoclada and C. mole were carried out to assess tree responses to varying intensities of livestock grazing and the compounding effects of fluctuating soil moisture in their natural conditions. On average, trees in the grazed fields (grazed plots) exhibited higher (P>0.0001) mean daily sap flux densities (SFD) compared to those excluded from grazing (fenced plots), amounting to 27.47 ± 8.65 g m-2s-1 and 20.17 ± 7.27 g m-2s-1, respectively. The peak daily sap flux densities were recorded around midday in both species. For both species, daily SFD was correlated (R2=0.77) with vapor pressure deficit. Seasonal changes in SFD were however positively influenced by the amount of rainfall, through changes in soil moisture. Higher SFD in the grazed plots was attributed to higher projected crown area. The diurnal variation in SFD showed that sap flow was coupled to the atmosphere with relatively low boundary layer resistance and the seasonal variation in sap flow was controlled by stomatal regulation. These findings point to the possibility that the dominant tree species in Lambwe are isohydric species.

The purpose of this article is to propose a hybrid deep learning framework for the effective detection of SQL injection (SQLi) attacks in database-driven web applications. The proposed framework integrates supervised and unsupervised learning techniques with honeypot-assisted intelligence collection to address the limitations of existing SQLi detection systems, which are largely reactive and primarily focused on classification accuracy without adaptive intelligence mechanisms. The architecture combines a CNN–LSTM pathway for supervised pattern recognition with an autoencoder-based anomaly detection pathway trained on benign queries. Outputs from both pathways are fused through a learned fusion layer to improve robustness against both known and previously unseen attack variants. Queries classified as malicious are redirected to a low-interaction database honeypot, enabling structured capture of attack payloads and behavioural artefacts for security intelligence generation. Experimental evaluation conducted on a curated dataset of approximately 50,000 SQL queries demonstrates strong detection performance, achieving an average accuracy of 99.2 per cent, precision of 98.9 per cent, recall of 99.0 per cent, and an AUC of 0.99 across multiple runs. Although the architecture supports closed-loop retraining using honeypot-captured data, this study focuses on offline performance and initial intelligence acquisition, with adaptive retraining identified as future work. The results demonstrate that integrating supervised learning, anomaly detection, and deception mechanisms provides a robust foundation for adaptive SQLi defence systems.

This study aims to explore the capacity of Artificial Intelligence (AI) to restructure the music royalty framework in Kenya. The research specifically investigates whether the deployment of AI can alleviate existing systemic issues within Kenya's music royalty distribution. Aligned with the Kenya Vision 2030 strategy, the music industry is recognised as a pivotal economic sector; however, its potential is currently constrained by the deficiencies of its collective management organisations (CMOs). These deficiencies primarily involve the ineffective utilisation of technology for royalty collection, a lack of transparency in reporting artist royalty payments, and governance challenges that have eroded artists' trust in CMOs. By adopting a documentary analysis approach within a theoretical framework to synthesise findings from international intellectual property case studies, KECOBO audit reports, and relevant legal frameworks. This comparison aims to compare global best practices for AI implementation against the structural limitations prevalent in Kenya's music industry. Furthermore, the study applies Giddens' Structuration Theory to analyse how the current manual systems perpetuate inefficiency through recursive processes within the music industry. The study also proposes a model where AI catalyzes "re-structuring," facilitating new norms of algorithmic accountability and providing new resources of verifiable data. The findings indicate that while various AI technologies could be applied to track and distribute royalties in Kenya, their successful implementation is hindered by challenges related to data infrastructure and digital literacy. This research concludes that a phased approach to AI adoption should be pursued, positioning AI not only as a tool for increased efficiency in music royalty distribution but also as a mechanism to restore artist agency and institutional trust.

Prolonged mechanical ventilation (PMV) remains a significant clinical challenge in intensive care units (ICUs). Approximately 30% of ventilated patients require PMV with attendant risk for higher morbidity, mortality, and healthcare expenditure. In spite of progress in critical care, little is known about the predictors and outcomes of PMV in low-resource settings. This study investigated the prevalence, demographic and clinical risk factors, and outcomes of prolonged mechanical ventilation in ICU patients at Tenwek Hospital. A retrospective cohort design was employed, reviewing medical records of adult ICU patients (≥18 years) who received invasive mechanical ventilation for more than seven consecutive days between January and December 2024. Patients were included if they had complete clinical documentation, ventilator parameters, and outcome data; those receiving only non-invasive ventilation or with missing critical records were excluded. Descriptive statistics and inferential analysis were used to analyse data. All associations were tested at p < 0.05. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were reported, with model stability ensured by maintaining a minimum of 10 events per predictor variable. Among 173 mechanically ventilated adults, 72.3% experienced prolonged mechanical ventilation. Multivariable logistic regression pinpointed acute respiratory distress syndrome (ARDS; adjusted OR = 5.25, 95% CI: 2.35-11.75) and chronic obstructive pulmonary disease (COPD; adjusted OR = 5.28, 95% CI: 2.38-11.73) as the strong predictors, followed by pneumonia (adjusted OR = 1.82, 95% CI: 0.80-4.14) and sepsis (adjusted OR = 1.56, 95% CI: 0.69-3.52). Daily sedation vacation reduced the odds of PMV by 81% (adjusted OR = 0.19, 95% CI: 0.08–0.46), while early mobility protocols diminished them by 37% (adjusted OR = 0.63, 95% CI: 0.28-1.42). These findings underscore the high burden of prolonged ventilation and recommend that simple, low-cost interventions such as structured sedation breaks and early mobilisation may significantly reduce the duration of ventilation and improve outcomes.

Asthma is a severe respiratory illness affecting all age groups globally. It is estimated that 18% of the population, which is around 262 million people, are affected, experiencing recurrent episodes of wheezing, chest tightness, and shortness of breath. It is the main cause of morbidity and mortality in children, measured by school absenteeism, emergency visits, and hospital admissions. For patients with asthma, exacerbations and poor control can result from a complex interplay between genetic predisposition and environmental immunity modifiers that can be grouped as biological and physical factors that include (genetics, endotoxin, pollutants, microbes, and aeroallergens). The psychological environmental factors like stress, neighborhood safety, discrimination, and housing have been noted to influence asthma. The objective of this review is to make a summary of various international literature written on aspects of both home and school environments and their effects on asthma prevalence, and to determine whether the environment plays a great role in achieving control. Literatures from 1995 to 2019 in the area of environment in relation to childhood asthma were identified by use of PubMed and Google Scholar, using the key terms: childhood asthma, asthma, and environmental effects. A reference list of all retrieved articles, related articles, and author names were used to expand the search that was used for this review. A conclusion was made that, despite the various treatment guidelines and medications available, the kind of environment children are exposed to plays a very significant role in attaining control and reducing exacerbations.

The aim of this study is to establish the relationship between country-club leadership style and job satisfaction amongst junior school teachers. Job satisfaction in education is essential for the attainment of good performance; therefore, there is a need to employ an appropriate leadership style that ensures teaching and non-teaching staff are satisfied beyond achieving good performance. The study was guided by Herzberg's two-factor theory of motivation, it adopted a correlational research design. Target population was 283, stratified and random sampling were used to obtain a sample of 180 participants. Pilot study was conducted to assess the reliability of the tools, and a Cronbach's alpha of 0.816 was attained, which is an acceptable limit. Quantitative data were analysed using descriptive statistics, while inferential statistics of the Pearson correlation coefficient were used to show the strength of the relationship between variables, and thematic analysis was used for Qualitative data from interviews. The country-club leadership accounted for 6.5 per cent of the variance in job satisfaction among the teachers in Mogotio sub-county (R Square 0.065); thus, 93.5 per cent of the variance in job satisfaction was explained by other factors. The F-test statistic (F = 7.664, p = 0.007) showed the fitness of the regression model, showing that country-club leadership style had a generally positive effect on teacher job satisfaction. Results of the study are useful to the Ministry of Education, the Teachers Service Commission, policy makers, the board of management and school administrators on leadership and management styles to increase teacher job satisfaction.

The purpose of this article is to investigate the influence of Entrepreneurial Orientation (EO) on the growth of Micro, Small, and Medium Enterprises (MSMEs) in Kenya, which, despite their significant contribution to employment and GDP, continue to face persistent growth barriers and high failure rates. EO—defined by innovativeness, risk-taking, proactiveness, autonomy, and competitive aggressiveness—has been widely studied, but empirical evidence in Sub-Saharan Africa remains limited and context dependent. To address this gap, the study employed a sequential mixed-methods design, combining quantitative surveys of 284 MSMEs with qualitative interviews of 15 owners/managers. Correlation results indicated that proactiveness, risk-taking, and innovativeness were positively associated with growth, autonomy was negatively related, and competitive aggressiveness was weakly positive. Regression analysis confirmed proactiveness, innovativeness, and competitive aggressiveness as significant growth drivers, while autonomy exhibited a significant negative effect, and risk-taking was statistically non-significant. The overall model explained 60.2 per cent of the variance in MSME growth. Qualitative findings complemented these results by showing that risk-taking was often interpreted as survival-driven rather than strategic, and autonomy contributed to inefficiencies due to weak oversight. Conversely, innovativeness and proactiveness were consistently perceived as critical for survival and competitiveness. These findings highlight EO's heterogeneous and context-sensitive effects on MSME performance. The study contributes to theory by advancing a contextualised understanding of EO in emerging economies and provides practical insights for policy and management by recommending strategies to strengthen innovation, proactiveness, and structured autonomy among MSMEs.

Rheumatic Heart Disease (RHD), a complication of Beta-Hemolytic Streptococcal infection, is a leading cause of cardiovascular mortality globally, particularly in Sub-Saharan Africa (SSA). While prevention strategies are increasingly emphasized, there is a recognized gap in assessing clinicians’ knowledge, attitude, and practice (KAP) towards RHD prevention, especially in high-burden settings like Kenya. This study aimed to evaluate the KAP of clinicians regarding RHD prevention in Chepalungu, Bomet County, addressing this specific research gap. This was a cross-sectional study involving 98 clinicians from peripheral facilities in Chepalungu, Bomet County, conducted over four months. Data were collected using a questionnaire that assessed demographics, knowledge, attitude, and practice related to RHD prevention. Data analysis involved descriptive statistics (frequencies and proportions), Odds Ratios, and Chi-Square tests to determine associations between variables. Most participants demonstrated good overall knowledge, attitude, and practice concerning RHD prevention. However, critical knowledge gaps were identified in areas vital for patient management. Specifically, only 4% (4 out of 98 participants) had good knowledge of the diagnostic tests for bacterial pharyngitis and the correct duration of antibiotic prophylaxis. A statistically significant relationship was found between knowledge and practice (CI 95%, p=0.024) and between attitude and practice (CI 95%, p=<0.001). The study reveals generally positive attitudes and practices towards Acute Rheumatic Fever (ARF) and RHD management, but also highlights significant knowledge deficits among clinicians. These findings underscore the critical need for continued medical education and ensuring accessible treatment guidelines across all healthcare levels to enhance RHD prevention efforts.

The precolonial pastoral economy is mainly subsumed to comprise of a community of people wandering with their drought-stricken cattle in search of pastures and water over long distances. The Kipsigis, who were initially a purely pastoral community and finally settled in a well-watered area around Kericho, gradually adopted crop production and supplemented their diet with agricultural produce, thus becoming mixed farmers. They nevertheless retained their indigenous knowledge in cattle herding and before the advent of colonialism, they were well known for their great attachment to and love for their cattle. The ‘cow’ was a central defining feature in their socio-cultural, economic and political organization and relations. This paper seeks to provide historical insights on the knowledge and practice of animal husbandry among the precolonial Kipsigis community in the Rift Valley to underscore the importance and resilience of Indigenous Knowledge Systems in a pastoral setting. It examines the variety of pastoral systems, the diversity on animal production and the dynamic animal-based food processing and storage techniques in forestalling food scarcity. It also examines the broad social mechanisms concerning animals in alleviating food shortages and famines. It is demonstrated that the Kipsigis precolonial pastoral systems were dynamic, innovative, diverse, efficient, self-reliant and suited to the needs of the people involved. It is argued further that the Kipsigis pastoral organization was sound, resourceful, and rational and based on the people’s knowledge of their environment.