Jaramogi Oginga Odinga University of Science and Technology

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.

A field experiment was carried out during the 2024/2025 season at Baraka Farm in the Lanet area of Nakuru County, Kenya, approximately 10 kilometers northeast of Nakuru city center. The study aimed to evaluate the effects of different fertilizers, BSF frass (black soldier fly excreta), KUZA, and NPK 17:17:17 on the growth, yield, and postharvest quality of the Chandler strawberry variety under field conditions. A randomized complete block design (RCBD) with three replicates was used. Data were collected on the number of leaves and flowers, plant height, yield, total soluble solids (TSS), firmness and titrable acidity. Results indicated that the number of leaves and flowers per plant, plant height was significantly (p ≤ 0.05) influenced by both season and fertilizer treatment. NPK (17:17:17) consistently produced the highest leaves counts at all growth. High fruit firmness values were obtained in the strawberries subjected to NPK 17:17:17 followed by BSF frass. BSF frass also resulted in relatively high acidity suggesting it can maintain acidity close to that of NPK. Application of frass, particularly from BSF frass substrates, led to improved strawberry vegetative growth, higher yields, and enhanced postharvest fruit quality. The study offers important insights into the potential of BSF frass as a suitable organic fertilizer, its role in reducing synthetic inputs and its contribution to improving both productivity and quality of strawberry.

While the growing accessibility of technology improves usability, it also creates more opportunities for cybercriminals to exploit vulnerabilities, significantly accelerating the proliferation of cybersecurity attacks. Deep learning (DL) approaches present significant advancements over conventional machine learning (ML) techniques by automating feature selection and extraction while minimizing external dependencies. This study proposes a deep learning-based model to enhance cyberattack detection and ensure that data security goals are achieved. This study employs a quantitative research design, utilizing simulation and modeling as the primary analytical tools. The dataset used is the Canadian Institute for Cybersecurity Intrusion Detection System (CIC-IDS-2017) dataset. Three distinct DL algorithms are used to design the detection models, namely, Deep Neural Network (DNN), Long Short-Term Memory (LSTM), and Recurrent Neural Network (RNN). The performance comparison metrics are F1-score, accuracy, sensitivity, false positive rate (FPR), specificity, positive predictive value (PPV), false negative rate (FNR), and negative predictive value (NPV). Optimization concepts are integrated to enhance the detection efficiency in web-based systems, including loss functions, gradient-based optimization, and efficient model generalization techniques. The results of k-fold cross-validation show LSTM’s higher scores for F1-score (94.6%), recall (94.7%), accuracy (94.8%), and precision (94.6%). LSTM outperformed RNN and DNN, achieving the highest accuracy, precision, specificity, and sensitivity at 94.7%, 94.3%, 98.9%, and 94.7% respectively, validating LSTM's superior generalizability for cyberattack detection tasks.

The length-weight relationship and condition factor of Clarias gariepinus fed on black soldier fly-based diets were studied for twelve weeks in winter. Five isonitrogenous and isolipidic experimental diets were formulated to contain different levels of black soldier fly larvae (0%, 25%, 50%, 75% and 100%). The meal with 0% BSFLM was used as a control. A randomised complete block design was used, and a total of 600 (0.46 ± 0.02g) unsexed Clarias gariepinus fingerling samples were randomly selected and stocked at a rate of 40 fish per plastic tank. The total length and weight were taken once every fortnight for the estimation of the length-weight relationship and condition factor. Length-weight relationship (LWR) was described by the equation: W = a Lb. The value of the regression coefficient obtained b from the WLR was 0.98, 0.98, 098, 0.97, 0.90, and 0.90, respectively. There was a significant correlation between length and weight, while the condition factor computed for Clarias gariepinus was 1.00, 1.00, 0.99, 0.99, and 0.95, which indicated good health condition during the experiment, and it indicates an isometric growth, which is desirable for fish in a fish farm. The experiment concluded that the cultured C. gariepinus using black soldier fly larvae-based diets were in good condition and healthy, and all the diets will be suitable for the commercial production of C. gariepinus.

Purpose: This study examines the influence of green banking defined as green lending, green bonds, ESG-aligned lending standards, and sustainable finance adoption on the financial performance of commercial banks listed on the NSE. Methodology: The study applies a positivist philosophy and correlational design using secondary data (2021–2023). Regression, diagnostic tests, and hypothesis testing were conducted using bank-level audited financial and sustainability reports. Findings: Green banking shows a positive but statistically insignificant effect on ROE (β = 0.114; p = 0.103). Diagnostic tests reveal non-normality, weak linearity, and low R², indicating immature adoption and inconsistent ESG reporting. Unique Contribution to Theory, Practice and Policy: Strengthen regulatory incentives, standardize ESG reporting, develop green-lending capacity, expand green bond markets, and embed climate-risk assessments into lending operations.

Purpose: The purpose of this study was to examine the influence of ecosystem banking on the financial performance of commercial banks listed on the Nairobi Securities Exchange (NSE). It aims to determine how ecosystem integration through partnerships with FinTech firms and digital platforms affects banks’ profitability and sustainability. Methodology: Adopting a positivist research philosophy and explanatory design, the study utilized secondary data from annual financial reports and sustainability disclosures of 11 listed commercial banks covering the period 2021–2023. Descriptive statistics, correlation, and multiple regression analyses were employed to assess the relationship between ecosystem banking and financial performance, measured by Return on Equity (ROE). Findings: The regression results revealed a negative but statistically significant relationship (β = -0.895, p = 0.016), indicating that ecosystem banking initially constrains profitability due to high technological and integration costs. Nonetheless, long-term benefits such as improved efficiency, innovation, and customer reach outweigh these short-term effects. Unique Contribution to Theory, Practice and Policy: The study recommends that commercial banks adopt phased digital transformation strategies and strengthen governance frameworks to enhance oversight of ecosystem partnerships. Regulators should formulate comprehensive digital finance policies that foster innovation while safeguarding consumer protection and systemic stability.

The purpose of the study was to examine the relationship between self – efficacy and interpersonal nature among orphaned adolescent students in secondary schools in Nyatike Sub - County, Kenya. The study was informed by Self-efficacy theory adopted from Bandura’s Social Cognitive Theory. Mixed Methods research design within Mixed Methods Approach was utilized and Concurrent Triangulation was used. The target population consisted of 1703 students, 17 teachers and 3 Focus Group Discussions from 57 public secondary schools in Nyatike Sub- County of Kenya. A sample size of 511 students, 17 teachers and 12 participants for Focus Group Discussions were obtained using stratified random sampling and purposive sampling techniques respectively. Reliability of instruments was determined through pilot study with 42 participants. The partici-pants in the pilot study were excluded from taking part in the actual study. Content and face validity of the instruments was ascertained by pilot testing of the questionnaires and also by seeking expert opinion of uni-versity lecturers experienced in formulation of research tools. Data was collected using closed-ended ques-tionnaires, in-depth interviews and Focus Group Discussions. Quantitative data was analyzed using descriptive and inferential statistics while qualitative data was analyzed using thematic framework. The study findings revealed that there was moderate positive (r=0.370, p=0.01) correlation between self – efficacy and interper-sonal nature of orphaned adolescents. The study concluded that self-efficacy could be enhanced to foster better interpersonal functioning among orphaned adolescent students.