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Design of an evaporative cooling system integrated with ultraviolet light for preservation of fruits and vegetables at variable tropical weather conditions: a case study of Arusha, Tanzania
Get PDFA Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Master’s in Sustainable Energy Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyProblems with fruits and vegetables spoiling after harvest are particularly acute in tropical
regions. This research presents the design, construction, and performance assessment of a
solar-powered evaporative cooling storage system incorporating ultraviolet radiation (UV) to
preserve foods susceptible to spoilage. Local materials, including sisal, sponge, and bricks, were used to construct the cooling chamber with a UV bulb. We measured the system's
efficiency in both sunny and overcast tropical weather conditions by looking at how much air
temperature was reduced, how much relative humidity was increased, and how much
electricity was used for evaporative cooling. According to research, fruits and vegetables may
be kept fresh for much longer after activating the UV light. This method may keep perishable
goods for up to 21 days under UV light and 9 days without. An average temperature drop of
5.0℃ and an increase in relative humidity result from active system operation on sunny days. In contrast, the cooling effect is minimal on overcast days, leading to a relative humidity rise
of 18% and a temperature drop of around 3.5℃. Based on these results, a solar-powered
evaporative cooling system with UV radiation treatment might be a good way to reduce
tropical post-harvest losses
A comprehensive review on the distribution of per- and poly-fluoroalkyl substances in the environment across Sub-Saharan Africa revealed significant variation in their concentrations
Get PDFThis research article was published by Environmental Challenges ,Volume 16 (2024)Per- and polyfluoroalkyl substances (PFAS) are a group of synthetic chemicals known for their widespread use in various industrial and consumer products. They enter the food chain via contaminated water, air, and soil, resulting in bioaccumulation in plants, fishes, foods, human milk, and blood serum. Here, we critically reviewed the literature published from 2005 to 2021 on the occurrence and distribution of Perfluorooctanoic acid (PFOA) and perfluoro-octane sulfonate (PFOS) as the most occurring PFAS in the aquatic environment in sub-Saharan Africa (SSA). To our knowledge, this is the first paper to review the status of PFAS in the SSA environment. This review found that almost all matrices studied in SSA regions have been polluted by PFAS with varying concentrations. This information suggests that the levels of PFAS in the environment deserve immediate attention. Furthermore, SSA faces unique challenges in understanding and managing PFAS contamination due to the scarcity of data in specific regions and the need for more administrative guidelines for monitoring PFAS in water. This review provides vital baseline information on the occurrences, distribution and contributing factors for their distribution in the SSA environment for better understanding to protect the environment and public health, and to develop sustainable solutions for the PFAS growing concern
More than pollutant removal: constructed wetlands and waste stabilization ponds as biodiversity hotspots and community assets in Tanzania
No full textA Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Environmental Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyWaste stabilization ponds (WSPs) and constructed wetlands (CWs) are important
ecotechnologies for wastewater treatment. Despite their potential and wastewater management
being challenging in urban and peri-urban areas of Tanzania, their adoption and sustainability
is not well developed. This study examined (a) social knowledge, attitude, and perceptions
(KAPs) on wastewater treatment, technologies involved, and reuse across municipal
wastewater treatment plants in four regions of Tanzania; (b) biodiversity of birds, insects, and
reptiles in constructed wetlands (CWs) and waste stabilization ponds (WSPs), and (c) bacterial
abundance and diversity in different types of CWs. A semi-structured household-level
questionnaire (n=327) was used to collect quantitative and qualitative data. The survey
involved observations and face-to-face interviews to assess social KAPs on wastewater
treatment, technologies, reuse, and potential health risks. Key informants were selected
purposively (n=8). The study also employed point counts, direct observations, and camera traps
to assess bird diversity in WSPs and CWs. Direct observation and pitfall traps along established
transects were used to collect and assess insects and reptiles. Fishnet was used to assess the
reptiles living in the WSPs. Additionally, wastewater was collected in four different CWs for
bacterial diversity establishment. Community KAPs were analyzed using SPSS, while Jamovi
and PAST software were used to analyze the diversity and abundances of birds, insects, and
reptiles, whereas bacterial community composition was characterized using Illumina-based
sequencing of the V3 and V4 hypervariable region of 16S rRNA. The results show that social
KAPs surrounding wastewater treatment and reuse were sufficient based on the KAPs score
achieved from the asked questions. However, the general knowledge of treatment technologies,
processes and reuse risks was found to be low. Over 90% of respondents were unaware of
wastewater treatment technologies and the potential health risks associated with using treated
wastewater (59%). Multivariate analysis of variance revealed significant differences (P < 0.05)
in KAPs for treated wastewater across different demographic variables examined, i.e., age, sex
and education level. Furthermore, results showed that birds exhibit high species abundance (n
= 1132), high species richness, Margalef index (D = 4.266), evenness (E = 0.815), Shannon
diversity (H = 2.881) and Simpson index (λ =0.903). The abundance and diversity of studied
groups differed significantly (P<0.05) between WSPs and CWs. In addition, the results showed
that the Proteobacteria were dominant (48.66%) phyla across all CWs. The
Gammaproteobacteria class (27.67%), the family Comamonadaceae (35.79), and the genus
Flavobacterium (4.35%) were dominant in all examined CWs
Solvothermal liquefaction of orange peels and catalytic upgrading of biocrude into transportation fuel over a hybrid catalyst
Get PDFA Thesis Submitted in Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Materials Science and Engineering of the Nelson Mandela African Institution of Science and TechnologyThe efficient valorization of biomass for energy-derived biocrudes is essential for effective
waste management. However, the production of biocrudes with high energy and reduced
oxygen contents during the liquefaction process requires further improvement. This study
investigates the impact of reaction temperature, residence time, and ratio of ethanol to acetone
on the energy compositions and bio-product’s yield enhancement were investigated under non catalytic and catalytic process with further upgrading. The biocrudes obtained via the non catalytic liquefaction were characterized for elemental composition, bio-oil compositions,
functional group, molecular weight and thermal stability to understand the effects of process
parameters on the biocrudes’ compositions. An improved bio-oil with High Heating Value
(HHV) (38.18 MJ/kg) and lower oxygen: carbon (O/C) ratio (0.11) were obtained at 430 ◦C,
35 min and 50% ethanol with a significant boost in the enhancement factor, deoxygenation,
and percentage hydrogenation of 2.63, 36.88%, and 77.87%, respectively. The presence of
ketones with composition of 32.58 area% suggests the needs for the removal of oxygen from
the bio-oil. Using a central composite design (CCD), catalyst dosage (3-6 wt.%) and reaction
temperature (330-430°C) were optimized, maintaining constant orange feedstock weight (10g),
reaction time (15 minutes), and a solvent ratio of 3:1 (acetone to ethanol). Optimal biofuel yield
(71.09 wt.%), solid residue (28.18 wt.%), biomass conversion (71.82 wt.%), and gas yield
(40.14 mL/g) were achieved at 430°C and 3 wt.% catalyst loading. The Fe/CNSs catalysts
possess high selectivity to acid formation. High correlation coefficients indicated the model’s
strong fit with experimental data. The hydrodeoxygenation (HDO) of cyclohexanone under
both catalytic and non-catalytic conditions involved mechanisms such as hydrogenation,
decarboxylation, decarbonylation, and dehydration. The NiCeMo catalysts shows an even
particle dispersion where 11.3 area % of hydrocarbon and highest conversion of ketones and
phenols were obtained. However, the performance of NiCeMo catalysts for HDO was
hampered by the Guerbet reaction, which led to the formation of side products which are
primarily alcohols. Modifying the acidity and using water as a solvent could potentially
increase the HHV of the biofuel hence, promote the usage for transportation purposes. Biofuel
produced through the non-catalytic process demonstrated a higher energy value of 38.18
MJ/kg, highlighting orange peels as a viable renewable energy resourc
The Artificial Neural Network-Based Smart Number Plate for Vehicles with Real-Time Traffic Signs Recognition and Notification
Get PDFThis research article was published by Springer Nature Link 2024The world is advancing technologically in all sectors, including intelligent transportation, whereby various vehicles’ movements are monitored and controlled remotely. These technologies simplify the tasks in traffic control and increase road safety. The previous related works implemented and designed provided different technologies that can identify, locate, and detect the vehicle’s speed. However, even though these technologies have been implemented, there is still a lack of assistance to drivers for earlier knowing the road situation and real-time accident notification to dedicated authorities such as traffic police stations. In this paper, an Artificial Neural Network-based Smart Number Plate with real-time traffic sign recognition and notification was developed. The developed number plate comprises two units, the processing unit and the display unit, which both communicate through wireless communication. The processing unit contains a speed sensor and vibration shock sensors, Global System for Mobile Communication (GSM), Global Position System (GPS), and Raspberry Pi 3 B+ that act as the system controller. The display unit contains the Expressif board, Liquid crystal Display (LCD), and Buzzer. With the TensorFlow model for machine learning, the smart number plate classifies and recognizes traffic signs with real-time notification. Moreover, this number plate had been tested on different drivers and assisted them in obeying the traffic signs earlier, and the traffic station had been alerted for emergency support
Uncovering service gaps and patterns in smallholder dairy production systems: A data mining approach
Get PDFThis research article was published by Science Direct Volume 26, December 2024Traditional clustering algorithms have often been used to categorize farmers but tend to overlook
the underlying reasons for these groupings. Typically, clusters are formed based on common
metrics such as dispersal and centrality, which provide limited insights into the relationships
among key attributes. This study introduces an innovative approach using pattern and association
rules analysis to better understand the characteristics of dairy production clusters. Focusing on
Tanzanian smallholder farmers, the research moves beyond identifying clusters to uncovering the
hidden relationships within them. Through pattern analysis, the study logically examines the
behavioral mechanisms that define these clusters, highlighting service gaps that, if addressed,
could enhance smallholder dairy farmers’ productivity. Frequent patterns with support ranging
from 57 % to 93 % and confidence levels between 85 % and 100 % were identified, revealing
critical challenges faced by these farmers. For instance, farmers using Artificial Insemi-
nation—typically younger or new entrants—face constraints related to farm size, land holdings,
fodder production, lack of farmer groups, and insufficient formal training in dairy care. Mean-
while, seasoned farmers deal more with institutional barriers such as limited access to market-
places, extension services, and distant water sources. The study highlights the diverse challenges
faced by different farmer groups and provides strategic recommendations for improving dairy
productivity. Enhancing access to formal training, improving fodder production, supporting the
formation of farmer groups, and addressing institutional barriers are key actions that could help
Tanzanian smallholder dairy farmers increase milk yield and overall productivity
Factors associated with poor compliance to rabies post-exposure prophylaxis among dog bite victims in Maswa District in Tanzania: a cross-sectional study
Get PDFThis research article was published by PAMJ One health volume 14, 2024Introduction: administering rabies post-exposure
prophylaxis (PEP) in a timely and appropriate
manner remains the most fundamental measure
for preventing human rabies. However, a number
of barriers to accessing and completing PEP exist.
Methods: a cross-sectional study was carried out
from April to July 2022 to examine individual and
societal barriers to accessing human rabies PEP in
Maswa in Maswa District, Tanzania. Dog bite
patients were interviewed to gather information
about the circumstances of the bite, as well as the
availability, affordability, and compliance with
PEP. Descriptive and inferential analyses were
conducted to address the research question.
Results: of the 264 bite patients, 57.6% were male
and 67.2% were under 15 years old. Dog bites
accounted for the highest proportion of cases
95.5% (n=252) and category-III bites were most
frequently observed 63% (n=167). About 45.1%
(n=119) of patients traveled over 25 kilometers
(km) from their residences to reach PEP clinics. The
average cost for obtaining PEP doses was USD
51.1. Only 3.8% (n=10) of patients received all five
recommended PEP doses. Travel distances and
costs were significant factors for poor PEP
compliance. Patients who traveled by bicycle to
health facilities had higher odds of PEP compliance
(aOR =17.12: 95% CI: 14.12 - 23.42) than those
who walked (aOR = 6.88: 95% CI: 1.28 - 26.13).
Furthermore, patients who utilized buses were four
times more likely to comply to PEP (aOR = 4.23,
95% CI: 1.06 - 16.46) than those using motorcycles.
Bite patients from urban areas were 6 times more
likely to complete the recommended PEP (aOR =
5.79, 95% CI: 1.29 - 15.20) than their rural
counterparts. Conclusion: findings from this study
inform measures to improve compliance to rabies
PEP among dog bite victims. These measures
include subsidizing the cost of PEP, improving PEP
accessibility, and raising awareness about the
dangers of rabies particularly in seeking and
completing the recommended PEP focusing on
rural communitie
A brief history and prospects of sodium silicate-based aerogel - a review
Get PDFThis research article was published by Journal of Sol-Gel Science and Technology, Volume 112, 2024This review paper, A Brief History and Prospects of Sodium Silicate-Based Aerogel, aims to attract junior researchers and/or students interested in investing time and other resources to harness the overriding potential of silica aerogel. It will also invigorate the field experts for quick reference and areas of growth. This review provides solid evidence that the prospects for aerogel-based water treatment solutions and other potential applications are very optimistic than ever before. Early reports from the 1930s are reflected on, and current efforts are critically examined. Aerogel is a highly porous nanomaterial with more than 90% of its pores filled with air and can be assembled into nano-scale structures suitable for various applications. Current efforts in 2023 and 2024 include improving optical transmission through ambient pressure treatment to produce aerogels using a two-step sole-gel procedure and enable large scale industrial production/application. Historically, efforts have been made to improve the following aspects: (i) precursor preparation, (ii) gelation, (iii) aging, and (iv) drying. This brief review article intends to demonstrate the efforts made to: (i) synthesize a unique material (aerogels) with interesting properties using supercritical drying method; (ii) overcome the challenges caused by supercritical drying; (iii) modify the surface of a wet silica film prior to ambient pressure drying; (iv) regenerate the ion-exchange resin; (v) develop a single step sole-gel process to form a gel; (vi) synthesize optically transparent silica aerogels; (vii) prepare silica aerogel with the largest surface area by methods that are versatile, cost-effective, and not time consuming; (viii) investigate the recyclability of aerogels and manipulate their hydrophilicity or hydrophobicity and; and (ix) design aerogel-based water treatment system. This review article highlights the brief history and prospects of sodium silicate-based aerogels and its potential applications, particularly in water treatment. Critical issues affecting the large scale production of aerogels are also pointed out
Modeling and optimization of calcined bentonite replacement in the mechanical and durability properties of mortar
Get PDFThis research article was published by Cleaner Engineering and Technology Volume 23, December 2024Currently, pozzolanic materials are mostly recommended to improve the properties of cement composite materials and reduce environmental pollution, challenging the world owing to ordinary Portland cement (OPC) production. Bentonite is mostly available natural pozzolana, however, extensive studies conducted on other clays like kaolin and some studies reported that bentonite exists in a consolidated form which requires heating activation methods. Therefore, it is essential to investigate the properties of bentonite in detail for its sustainable use, and it is novel to model and optimize the optimum bentonite calcination temperature and time for the best performance replacement in mortar. Hence, the present study investigates the optimum bentonite calcination temperature, calcination time, and replacement dose for mortar strength and free lime using the central composite design-response surface method (CCD-RSM). The mortar was prepared by replacing the calcined bentonite with cement weight with different values of the factor variables, bentonite dose, calcination temperature, and calcination time. Durability tests were conducted after 56 days. Thus, the results indicate that the selected model of response variables for compressive strength and free lime were significant, accurate, reliable, and had excellent fitness to the experimental work. Hence, CCD-RSM predicted the optimum for independent factors of bentonite dose 19.99 %, calcination temperature 799.99 °C, and calcination time 135.04 min and experimentally validated, which improved the strength by 24.94% and reduced free lime by 3.08% compared to the control mortar, besides reducing CO2 emissions compared to OPC production, which requires 1450 °C. Furthermore, the optimized bentonite replacement parameters have highly enhanced durability in different environments such as water, acids, salt, and elevated temperature compared to the control mixture at the age of 56 days
A Review on NLP Techniques and Associated Challenges in Extracting Features from Education Data
Get PDFThis research article was published by International Journal of Computing and Digital Systems in August 2024There has been a significant increase in academic processes to ensure the quality of educational resources such as curricula,
examinations, and educational content. This has drawn attention to studies exploring the use of text mining, learning machines,
and auto-analytic tools like natural language processing (NLP) to interpret and evaluate the quality of these educational resources.
Auto-analytical techniques are required to evaluate the quality of educational content; otherwise, manual evaluation can be burdensome
and improperly influenced by human instincts. This study employs a methodical approach to comprehensively survey NLP techniques
for extracting syntactic and semantic features to analyze and comprehend educational content. NLP, in combination with machine
learning, is an ideal tool for automatically evaluating the aspects of higher education quality. This is because they include features
that aid in textual content comprehension as well as implementing natural language techniques that provide an interpretive interface
between humans and machines. The review highlights the limitations of NLP in evaluating educational data, including the need for
sentence-level understanding and the need for research to address challenges like noise in text data, domain-specific language variations,
and improving model robustness for effective feature extraction in educational contexts. The findings of this review hold substantial
benefits for various stakeholders, including education regulatory bodies, researchers, higher education institutions, and NLP researchers.
Notably, the study equips NLP researchers with valuable insights into document analysis’s current strengths and weaknesses. The
accumulated evidence can provide the skills to develop NLP-based applications for evaluating the relevant and quality aspects of
education in higher educational settings. Furthermore, NLP researchers can be updated on the strengths and limitations of document
analysis, allowing them to apply effective text representation approaches and implement the appropriate algorithm and techniques for
NLP tasks, particularly in educational data.
Keywords: NLP, syntactic features, semantic fea