University of Arusha

ABSTRACT With the rising demand for sustainable materials, the plywood industry is turning to bio‐resins as an eco‐friendlier alternative to traditional fossil‐based resins. However, the poor physio‐mechanochemical properties of the bio‐resins limit their applications. This study seeks to enhance these properties by integrating nanocellulose derived from sugarcane bagasse into cardanol formaldehyde resin. The resin was synthesized via polycondensation under acidic conditions, and nanocellulose was prepared using acidic hydrolysis. Nanocellulose was added at concentrations of 3%, 5%, 7%, and 10% to create reinforced nanocomposites, which were used to fabricate plywood panels and subjected to mechanical and physical properties tests. The modified resins were subjected to chemical and morphological tests. Results revealed significant improvements, with 7% nanocellulose resin achieving a peak breaking strength of 39.52 ± 2.1 MPa, compared to 13.16 ± 1.2 MPa for unmodified resin. While 10% nanocellulose reduced strength due to over‐interaction of the nanocellulose, all concentrations above 3% exceeded the 20 MPa industry standard. Thermal stability of the nanocomposite was enhanced, with decomposition and glass transition temperatures increasing to 473°C and 453°C, respectively. These findings underscore the potential of nanocellulose‐reinforced bio‐resins as high‐performance, sustainable materials for plywood manufacturing.

This study presents the simulation and design of a grid-connected single-phase photovoltaic (PV) system using PSCAD/EMTDC, specifically targeting the energy needs of Tanzania.This project explores the potential of solar energy as a sustainable solution to meet the growing energy demands in Tanzania, where energy access remains limited, with only 38% of the population having access to it.In this study, a 12-kW solar PV system was designed, incorporating MPPT controllers, DC-DC boost converters, and grid connection strategies.The simulation results show the effectiveness of the proposed system in maintaining power quality and optimising maximum power point tracking (MPPT) under varying solar irradiance and temperature conditions.The model meets international grid standards and demonstrates the feasibility of solar energy as a viable solution to the energy challenges in Tanzania.

This study aimed at developing an empirical model for estimating and analyzing CO2 reservoir performance. This was achieved by using decline curve analysis (DCA) to determine an accurate empirical decline model for reservoir performance prediction and optimal producing, i.e., time at which the plant recovery build-up (RBU) efficiency has declined to an approximate value of 44.5%. MATLAB R2013b was used for calculating raw gas density whereas Ms Excel 2007 was used in plotting and performing all calculations. Through an examination of real production data, a harmonic decline model with an Arps’ decline constant (d) of 1.0 and a nominal decline rate of approximately 0.035572337/year was identified as the most suitable for characterizing reservoir performance. The study identifies the year 2048 as an optimal opportunity for implementing production optimization strategies to maximize returns while ensuring efficient resource recovery. Acknowledging the limitations of DCA, the study recommends exploring alternative forecasting models such as type curve analysis (TCA), material balance equation (MBE), and well simulation techniques to mitigate uncertainties in reservoir performance prediction. In addition, the study proposes a 5-year model verification and improvement program to refine reservoir descriptions and enhance data acquisition practices, aiming to optimize production efficiency and minimize uncertainties in CO2 reservoir operations.

Soft Loans targeting youth in agricultural sector plays crucial role in reducing poverty as well as providing employment in Low-and Lower-Middle-Income countries (L&LMICs). However, Empirical evidences, revealed that youth-targeted soft loans and agricultural productivity in L&LMICs have mixed effects. This article reviews the impact of youth soft loans to the agricultural productivity in L&LMICs. A systematic review was conducted using various search engines to access various databases which ended by obtaining 5 relevant articles published between 2015-2024. For article to be included for review was assessed using the following criteria; focused on youth population, assessed soft loans, measured agricultural productivity, conducted in L&LMICS and peer reviewed. The review found that youth soft loan programs in L&LMICs, significantly enhance agricultural productivity as they led to higher yields, increased income, and job creation. Youth-targeted soft loan programs have the potential to significantly boost agricultural productivity and socioeconomic outcomes in L&LMICs when designed with accessibility, support services, and inclusivity.

In this study, we aimed to evaluate the accuracy of loan sanction predictions using two different algorithms. We analyzed how well each algorithm performs by applying them to a sample size of 20, divided equally into two groups. Group 1 used the KNN algorithm with 10 samples, while Group 2 used the Decision Tree algorithm with another set of 10 samples.To ensure the reliability of our results, we applied an independent sample analysis with a G power value of 80% and an alpha level of 0.05. The results showed that the KNN algorithm achieved an accuracy of 70.83%, whereas the Decision Tree algorithm performed slightly better with an accuracy of 74.47%. The difference between the two algorithms was statistically significant, with a two-tailed significance value of 0.032 (p < 0.05).

their low initial investment, simple design, ease of maintenance, and low head utilization. However, the technology suffers from poor performance issues caused by the non-optimized parameters of its crucial components, such as the runner. In this study, the performance of a runner (16° blade-hub angle, six blades, and a curved blade profile) for a GWVPP was experimentally examined. The study also employed an exergy analysis. The experimental results revealed that the efficiency of the GWVPP system was in the range of 9.84% to 25.35%, the torque was in the range of 0.08 to 0.23 Nm, and the output power was in the range of 2.96 to 7.33 W. Furthermore, an exergy analysis of the system showed an exergy efficiency of 43.58%. Additionally, the error analysis of the GWVPP revealed ranges of 0.1 - 0.5 W for power, 0.01 - 0.03 Nm for torque, and 1.3–3.1% for efficiency, suggesting that the experimental setup and instrumentation of this study were reasonably accurate. Based on the results, the new vortex runner and GWVPP system are recommended for energy generation in low-head, low-flow small hydropower plants. Keywords – Micro-hydropower; gravitational water vortex; runner; exergy efficiency; test rig