This work investigates the phytochemical analysis and antifungal activities of the methanolic leaf extract of Acacia nilotica. The phytochemical screening was carried out using a standard procedure to detect the presence of secondary metabolite which include: Alkaloids, Tannins, Flavonoids, Steroid and Anthraquinones. The extract undergoes thin-layer (TLC) and column chromatography to determine the active components. The fraction that appears more undergoes FT-IR analysis, which showed the most active compounds present in the Acacia nilotica. The antifungal assay of the active compound was conducted which inhibited the growth of Candida albicans by measuring the zone of inhibition at different concentration ranging from 0.25 mg/mL, 0.125 mg/ml, 0.0625 mg/mL and 0.03125 mg/mL respectively, fluconazole was used as positive control in Candida albicans, antifungal activities in Candida albicans showed zone of inhibition of 19 mm, 16 mm, 14 mm, 9 mm respectively and 34 mm at control. Thus, the analyses conducted confirmed the presence of various phytochemicals and antifungal properties of the plant.
HIV/AIDS remains a major public health challenge in Nigeria. Dermatologic and psychiatric manifestations are common but often under-recognized complications in people living with HIV (PLWH). This study assessed the occurrence and patterns of skin and psychiatric disorders among PLWH in Kaduna metropolis and examined their association with viral load suppression and antiretroviral therapy (ART). A cross-sectional study was conducted among 270 HIV-positive patients attending two HIV treatment centres in Kaduna State. Dermatologic diagnoses were made by a consultant dermatologist, while psychological distress was screened using the 12-item General Health Questionnaire (GHQ-12). Viral load and ART regimen data were extracted from clinical records. Associations were assessed using chi-square tests. Skin disorders were present in 51.5 % of participants. Papulosquamous disorders (13.3 %) were the most common. A significant association was observed between skin disorders and unsuppressed viral load (p = 0.008), as well as ART regimen (p = 0.038). Psychological distress suggestive of psychiatric morbidity was identified in 12 % of participants and was more frequent among those with skin disorders. Dermatologic manifestations remain common among PLWH in Kaduna and are significantly associated with virological control and ART regimen. Integrating dermatologic and mental health screening into routine HIV care may improve overall patient outcomes.
This study investigates the proximate compositions of seven fish and poultry feeds sourced from imported, local, and biotechnologically formulated agricultural waste in Nigeria. Using standard AOAC methods, parameters such as moisture, ash, protein, lipid, crude fiber, and carbohydrate were analyzed to assess their nutritional profiles. The results revealed notable variability across the samples, especially in ash, lipid, crude fiber, and carbohydrate contents. Moisture and protein levels, however, were relatively consistent and displayed near-normal distributions, which is advantageous for processing and storage stability. The statistical analysis uncovered significant relationships among the proximate components. A strong positive correlation (r=0.85) was found between protein and lipid contents, indicating that higher protein levels tend to be associated with higher lipid levels, possibly due to similar raw ingredient sources or formulation practices. Conversely, an inverse relationship was observed between crude fiber and carbohydrate contents (r=-0.78), suggesting that as fiber content increases, carbohydrate levels decrease substantially. Analysis of Variance (ANOVA) results confirmed significant differences in lipid and carbohydrate contents among the samples, highlighting the diverse nutritional profiles based on source and formulation. Regression models further supported these findings, revealing that increasing lipid and ash contents could positively influence protein levels, while reducing fiber could enhance carbohydrate content. The findings suggest that biotechnologically formulated feeds derived from agricultural waste have considerable potential as sustainable, cost-effective alternatives to imported feeds. These formulations can be optimized through fermentation, microbial enrichment, and standardization to ensure consistent nutrient levels. The study recommends scaling up these biotechnological processes, implementing standardization measures, and encouraging policy support to promote the adoption of such feeds. Ultimately, these strategies can help reduce Nigeria’s reliance on imported feeds, enhance livestock and aquaculture productivity, and promote climate-smart, sustainable animal feeding practices across the country.
Despite concerted global efforts to reduce child mortality, 5.3 million under-five deaths were reported in 2018, with Nigeria struggling to meet the Sustainable Development Goal (SDG) 3 target of 25 deaths per 1,000 live births by 2030. This study introduced a flexible proportional odds (PO) model, incorporating spatial random effects and covariate interaction Structures, to elucidate the complex relationships between factors influencing Under-Five Mortality (U5M) in Nigeria. Leveraging 2018 Demographic and Health Survey (NDHS) Data, the study evaluated the extended model against existing models, including those without covariate interaction, those without spatial random effects, those with Independent and Identically Distributed (IID) priors, and those with Intrinsic Conditional Autoregressive (ICAR) spatial priors. The results showed that the extended model: PO survival model with ICAR spatial prior and logistic transformed covariates interaction structure (LTCIS) outperformed existing models based on Log Pseudo Marginal Likelihood (LPML), Deviance Information Criterion (DIC), and Watanabe Akaike Information Criterion (WAIC). Key predictors of U5M include maternal age, breastfeeding duration, preceding birth interval, maternal education, wealth index, region, antenatal visits, pregnancy duration, child's sex, twin birth, mosquito net use, and contraceptive use. Notably, interaction effects revealed that higher maternal education levels amplify the benefits of breastfeeding on U5M. This study demonstrated the effectiveness of the proposed PO model in capturing the intricate dynamics of U5M, highlighting geographic and social clustering patterns that can inform targeted interventions to reduce under-five mortality in Nigeria.
The study investigates fruit waste – based diets as alternative feed sources for Tenebrio molitor (mealworm) larvae, using nutritional composition, cost-effectiveness, and larval growth performance. Pineapple peels (PP) and watermelon rinds (WR) were processed and analyzed for nutritional composition using standard protocols. Five diets were formulated: D1 (control: 100 g wheat bran), D2 (50 g wheat bran + 50 g PP), D3 (50 g wheat bran + 50 g WR), D4 (50 g wheat bran + 25 g PP + 25 g WR), and D5 (50 g PP + 50 g WR). Each group received 100 g of feed over 90 days. PP showed higher moisture, ash, fat, and crude fiber, while WR had higher mineral and energy content. D3 had the highest energy value (2330 kcal/kg). Feed cost decreased progressively from D1 to D5 (14,000 -5760), with D5 being the most cost-effective. Larvae fed D1 showed the best growth and feed efficiency, with an average larval weight of 237.40±31.25, followed by D4 (106.47±0.95), indicating that partial substitution maintained good performance. Complete replacement reduced growth, likely due to lower protein and higher fiber content. This supports the concept of sustainable waste valorization in insect production systems.
This study assesses bird diversity across selected urban environments, focusing on bird abundance, species richness, diversity metrics, and feeding guilds. A total of 247 birds were recorded, yielding an average of 41.17 ± 6.28 birds per site. Notably, residential sites exhibited the highest bird abundance (57.5 ± 4.5), while market sites had the lowest (28.5 ± 4.5). The Rock pigeon (Columba livia) emerged as the most prevalent species, highlighting its adaptability to urban habitats. A total of 19 species were identified, with the highest species richness recorded in residential areas (14.5 ± 0.5) compared to motor-park (4.5 ± 0.5) and market sites (3.5 ± 0.5). Statistical analyses indicated significant variations in species richness and diversity indices (F = 25.6689, P = 0.013), with residential areas demonstrating the greatest diversity (2.2865 ± 0.0845) and evenness (0.855 ± 0.02). The orders Columbiformes, Passeriformes, and Accipitriformes were the most widely represented. Feeding guild analysis revealed the highest granivore abundance in motor-park sites (31.5 ± 11.5), while residential sites supported the most omnivores (18 ± 0.0) and insectivores (18 ± 8.0). These findings underscore the importance of urban green spaces in supporting diverse bird communities and highlight the need for effective urban planning to enhance biodiversity in urban ecosystems.
Theileriosis is a significant tick-borne protozoal disease affecting equines in many tropical and subtropical regions. Clinical signs can vary from mild fever and anaemia to severe debilitation, depending on the species, strain, and host factors. This case report documents the diagnosis, treatment, and outcome of theileriosis in a 5-year-old Sudanese racing horse, Albadar, in Gumel, Jigawa State, Nigeria. A case presentation involved a 5-year-old male Sudanese racing horse that showed decreased exercise endurance, occasional high temperatures, pale mucous membranes, and a tick infestation. A clinical examination, haematology tests, blood biochemistry, blood smear examination under a microscope, and the response to mesotherapy all supported the diagnosis of theileriosis. Treatment entailed antiprotozoal therapy (Intramuscular imidocarb dipropionate (2.0 mg/kg) was administered for 48 hours), supportive care (fluid therapy and iron/vitamin supplementation), and acaricide application. The horse responded well with clinical improvement within 72 hours and full recovery within 3 weeks. Early detection, prompt antiprotozoal treatment, acaricide therapy, and supportive care can lead to positive results in equine theileriosis cases. Routine tick control and surveillance are crucial in Nigerian racing stables, as this case demonstrates.
Waste disposal is a major challenge confronting and threatening the environment globally. Heavy metals can be found in almost all planetary surroundings, such as dumping sites and biological activities. Contaminated soil and groundwater with these metals have turned into a serious issue for the residents and agricultural experts in Ibadan, because of the damage and havoc caused to human life and agricultural products. The five different samples were obtained from different groundwater and soil sites and then analyzed for elementals: Cadmium (Cd), Manganese (Mn), Nickel (Ni), Chromium (Cr), Zinc (Zn), Cobalt (Co), and Lead (Pb); after acid digestion using Atomic Absorption Spectrophotometer, while physicochemical parameters (pH and conductivity) were also determined in soil and water samples. The samples of soil were taken in triplex at 15 cm intervals in depth, while the samples of water were collected from different hand-dug wells below 15 m deep. The following ranges results (in mg/kg) were obtained for soil samples: Pb (0.04-0.08); Cr (0.05-0.08); Cd (0.02-0.05); Zn (0.54- 4.49); Co (0.04-0.07); Mn (0.03-0.06) and Ni (0.06-0.13); while the pH ranged from (7.6-8.5); conductivity (406-683) uS/cm. The following values of results (in mg/L) were obtained for water samples: Pb (0.01-0.03); Cr (0.02-0.04); Zn (0.6-1.1); Co (0.01- 0.04); Mn (0.01-0.06) and Ni (0.02-0.03), but Cd was not found, while pH ranged from (6.3-6.9) and conductivity (264-607) uS/cm. The concentrations of Mn, Ni, and Pb in groundwater collected from Sango and Moniya were above the WHO/SON permissible limits. The results revealed that the concentrations of Ni, Co, Pb, Cr, and Cd in soil were above the WHO/SON acceptable bounds. Also, Mn and Zn were lower than the bound.
With the intention of protecting road users and network facilities, notable security challenges that require robust intrusion detection systems (IDSs) have been identified with the growth of vehicular networks. This systematic review examines recent deep learning (DL) applications to assess their capability to identify anomalybased intrusions in vehicular networks, with a focus on Gated Recurrent Unit (GRU) architectures. Following a structured literature search and screening protocol, peer-reviewed studies published between 2021 and 2025 were systematically identified, evaluated, and synthesized. GRU networks enable real-time detection with efficient computation and also show remarkable capacity to capture temporal dependencies and sequential patterns in network data. This systematic review finds that GRU-based systems can achieve better performance with fewer parameters and maintain low computational cost by effectively addressing the vanishing gradient issues in conventional RNNs. Some of the reported accuracies exceeded 99% across several benchmark datasets, including CICIDS2017, CICIDS2018, NSL-KDD, and UNSW-NB15. Hybrid GRU-CNN architectures routinely outperform traditional detection algorithms. The efficient utilization of GRUs in resource-constrained vehicle contexts is confirmed by performance tests using evaluation metrics such as precision, recall, F1 Score, and false positive rate (FPR). GRU ensembles, combined with other algorithms such as bidirectional LSTM networks, attention mechanisms, and optimization techniques, have improved detection capabilities against complex attacks such as DoS, blackhole, and zero-day exploits. The results show that GRU is crucial for developing an accurate, lightweight IDS that can be deployed to safeguard transportation infrastructure and current vehicular networks.
Annona muricata (soursop) is a tropical plant widely used in traditional medical practice for the treatment of various ailments, yet comprehensive safety data on its effects on vital organs remain limited. This study investigated the biochemical and histopathological effects of A. muricata leaf extracts on the liver, kidneys, testes and ovaries of albino wistar rats. Twenty adult albino rats weighing 180-200g were procured from the animal holding of the Department of Anatomy, University of Benin, and maintained under standard conditions with unrestricted access to feed and water. The rats were divided into four groups with each group consisting of 5 rats. The control Group A received distilled water only, while Group B was administered 250mg/kg of A. muricata extract; Group C received 500mg/kg, while Group D was given 1000mg/kg of A. muricata extract orally via gavage for one month. Following treatment, the rats were euthanised and blood samples were collected for biochemical analysis while organs were excised for histopathological evaluation. The result revealed no significant changes in haematological parameters, liver function tests, or reproductive hormone levels across all groups (p > 0.05). However, significantly elevated sodium and chloride levels were observed in rats administered 1000mg/kg/bw extracts of A. muricata when compared to the control (p < 0.05). Histopathological evaluation revealed normal histoarchitecture in the control rats, while rats administered with 250mg/kg/bw and 500mg/kg/bw of A. muricata exhibited hepatic steatosis with microvacuolar degeneration; however, rats administered with 1000mg/kg/bw of A. muricata maintained normal liver histology. All kidney, testis, and ovary sections demonstrated preserved normal architecture across treatment groups. Findings in this study suggest that A. muricata leaf extracts exhibit a complex doseresponse relationship, with the intermediate doses causing hepatic steatosis while higher doses appear protective. The preservation of the reproductive organ integrity and absence of a significant biochemical toxicity support the traditional use of A. muricata, though careful dose optimisation and electrolyte monitoring are recommended for therapeutic applications.
Data preparation remains a major bottleneck in analytics and machine learning workflows, often consuming up to 80% of the total project effort for data scientists. Although recent systems automate portions of the preparation pipeline, most lack mechanisms to capture or reuse user feedback, thereby limiting their ability to adapt to evolving data characteristics and domain-specific requirements. This study aims to systematically review the state of research on feedback-driven automation in data preparation, with emphasis on how feedback mechanisms are designed, integrated, and evaluated in contemporary systems. A systematic literature review was conducted following PRISMA 2020 guidelines, targeting peer-reviewed publications from 2010 to 2025 indexed in IEEE Xplore, ACM Digital Library, SpringerLink, Semantic Scholar, and Google Scholar. Twenty-nine primary studies met the predefined eligibility criteria and were included in the analysis. The findings indicate that feedback is predominantly utilised at schema-alignment, error-detection, and transformation stages, where explicit user input or implicit behavioural signals guide corrective processes. Feedback has been shown to improve data quality and reduce the need for repeated manual intervention; however, existing solutions are fragmented and do not support the persistence or reuse of feedback across future datasets or sessions. The review identifies a significant gap in unified architectures that treat feedback as a sustained knowledge asset. Addressing this gap presents opportunities for developing adaptive, feedback-driven data-preparation platforms that enhance transparency, reliability, and long-term automation benefits.
Artificial intelligence (AI) is a branch of computer science that deals with the research and development of simulating and extending human intelligence theory, methods, and applications in technical science. This study evaluates the contribution of AI tools to the development of mathematical algorithms and programming code for tidal analysis at the Bonny Port, Nigeria. The Twenty (20) best AI coding tools were employed for the retrieval of mathematical algorithms for long period tidal analysis, computations of orbital elements(s, h, P, N and P 1 ), astronomical argument (E), nodal correction (u) and nodal factor (f), formation of the Normal (N)matrix from the design (A) Matrix, inversion of the N matrix by Least Squares Method (LSM) and monthly tidal analysis for the year 2018. Results obtained from each of the 20 best AI tools were evaluated compared with each other using a Likert scale of 1-5 point rating scale method based on their significance. Also, the results from each of the 20 best AI coding tools were compared with the results produced by the Author’s code using the same Likert scale of 1-5 point rating scale method. Each of the 20 AI tools contributed its results that enhance this study, although to various degrees. The Author’s codes presented complete results of monthly tidal analysis in which tidal constants (H, g) for the 28 primary constituents of tide are presented and the monthly Mean Sea Level (MSL). This study shows that AI tools have brought advancements to the development of programming codes, but with some critical issues, such as the nature of some AI models and algorithms used, the interpretation of the codes, and accuracy. This study also shows that AI is augmenting human capabilities and reducing their workload. Therefore, it can be concluded that AI coding tools are enhancing the development of mathematical algorithms and programming codes, and also improving data processing and analysis for tidal analysis for the Bonny port, Nigeria. However, AI is not a replacement for human skills.
Guiera senegalensis is a well-known traditional medicinal plant in Africa, whose leaf extracts are used for the treatment of diseases and wounds. This study aimed to assess the phytochemical screening and antibacterial activity of the ethanolic leaf extract of Guiera Senegalensis. The plant material was macerated with ethanol to obtain crude ethanol leaf extract. The phytochemical screening revealed the presence of tannins, saponins, anthraquinone, alkaloids, phenolic, and flavonoid compounds. Thin-layer chromatography of the crude extract was carried out to ascertain the various fractions contained in the extract. In addition, column chromatography was carried out on the extract using ethanol as the mobile phase and silica gel as the stationary phase. Fractions from the extracts were collected, and the most active compound was used in the antibacterial studies. The FT-IR studies of the active compound revealed the presence of OH, CH, C=C, and C-O-C functional groups with the corresponding peaks of 3324, 2922, 1610, and 1073 cm -1, respectively The antibacterial assay of the active compound was conducted which inhibited the growth of S. aureus and E.coli by measuring the zone of inhibition of difference concentration ranging from 250 mg/mL, 125 mg/mL, 62.5 mg/mL and 31.25mg/ml respectively, Ciprofloxacin was used as positive control in both S. aureus and E.coli, antibacterial activities in S.aureus showed zone of inhibition of 14 mm, 12 mm, 9 mm 7 mm, respectively and 32 mm at control. Also, E. coli showed 15 mm, 12 mm, 10 mm, 9 mm, respectively, and 29 mm at the control.
The growing accumulation of biowaste in the environment, coupled with rising concerns about plastic pollution, has intensified interest in sustainable materials derived from renewable resources. Among such wastes, snail shell residues and water hyacinth biomass occupy a unique position as both environmental liabilities and valuable feedstocks for biopolymer production. This review synthesizes current literature on (i) contamination of snail shells and water hyacinth by heavy metals and persistent organic pollutants (POPs), (ii) extraction and characterisation of chitosan from snail shells and carboxymethyl cellulose (CMC) from water hyacinth, (iii) microbial load considerations affecting material safety and performance, and (iv) development of biodegradable bioplastics based on chitosan – CMC systems reinforced with oilpalm fibre. Emphasis is placed on understanding contaminant binding mechanisms, process optimisation strategies, physicochemical and functional properties of the derived polymers, and their suitability for high-value applications. Key challenges related to contamination risks, microbial safety, scalability, and market competitiveness of bioplastics are critically discussed. The review highlights research gaps and future directions required to enable safe, standardised, and economically viable valorisation pathways for these abundant bioresources within a circular bioeconomy framework.
There has been a recent surge in interest in studying molecular junctions made up of small acenes, such as anthracene, tetracene, and pentacene. Apart from the known transport properties exhibited by molecular junctions, there are other areas of interest, such as photothermal applications. Materials that can absorb and convert infrared radiation into heat energy can be applied in these areas. Density functional theory (DFT) calculations were used to evaluate the IR absorption of some acene-based MJs, as well as their rotational and translational energies. The results obtained were then compared with previously reported work on acene molecules. It is found that the total energy and maximum forces of these MJs converged, and the structures relaxed to the minimum possible energy. For the vibrational analysis, the maximum IRabsorption of 4.92 D 2 /Å 2 was observed at a frequency of 688.52 cm -1 for an anthracene MJ. It is 2.17 Debye square per Armstrong square (D2/Å2) at a frequency of 3411.82 cm-1 and 2.93 D2/Å2 at a frequency of 648.71 cm-1 for tetracene and pentacene MJs, respectively. IR absorption at different frequencies enables one to choose the desired materials for a specific task at a given frequency.
Under-five mortality remains unevenly distributed across communities in developing economies, reflecting disparities in socioeconomic conditions, maternal characteristics, and access to basic health services. This study examines the determinants of under-five mortality across five administrative divisions of Lagos State, Nigeria, using a prognostic regression framework that aligns with the distributional properties of mortality data. The primary outcome was the number of under-five deaths experienced by a woman, while a secondary outcome captured whether any underfive death occurred. Explanatory variables included socioeconomic status, maternal education, healthcare access, nutritional status, sanitation, immunization coverage, and community of residence. Binary logistic regression was used to model the probability of experiencing any under-five death, while Gaussian and Gamma regression models were applied to mortality severity. Model selection using Akaike and Bayesian Information Criteria identified the Gamma regression model as most appropriate. Results indicate that improved socioeconomic status reduced expected under-five mortality by approximately 68%, while enhanced healthcare access and sanitation reduced mortality by about 57% and 49%, respectively. Each additional year of maternal education reduced expected mortality by about 6%, whereas poor nutritional status significantly increased risk. Marked spatial disparities were observed, with Ikorodu, Badagry, and Epe exhibiting higher mortality burdens. Overall, the findings reveal the importance of distribution-aware prognostic modeling and targeted communityspecific interventions to reduce under-five mortality in Lagos State.
Curcuma longa L. (Zingiberaceae) is a widely utilized medicinal plant, known for its anti-inflammatory, antioxidant, antimicrobial, and hepatoprotective properties. While rhizome-based pharmacology has been extensively studied, leaf bioactivity remains underexplored. This study investigated the phytochemical composition of the leaf extract of Curcuma longa using standard qualitative tests and Gas Chromatography – Mass Spectrometry (GC–MS). Phytochemical screening revealed the presence of flavonoids, tannins, saponins, terpenoids, glycosides, and phenolic compounds. GC–MS analysis identified major constituents including ergosterol (18.03%), n-hexadecanoic acid (10.51%), oleic acid ( ⁓ 10.22%), stearic acid (6.62%), phytol (0.70%), and squalene (0.57%). These bioactive compounds are reported to possess antioxidant, antimicrobial, and anti-inflammatory properties. This study characterises the chemical constituents identified in the leaves of Curcuma longa and highlights their potential as a source of bioactive compounds with possible pharmacological relevance.
In this paper, we seek to improve an earlier replacement model that uses dynamic programming to analyze the impact of depreciation on state-owned vehicles. A common assumption associated with the model is that all return functions and decision possibilities are uniform or identical. The method of finite differences is applied to determine the optimal replacement time for automobiles whose economic value deteriorates over time, thereby increasing maintenance and operating costs. The objective of the model is to minimize the average yearly cost of operating vehicles whose costs of maintenance increase with time, while the scrap value is constant. It is assumed that the time value of money is negligible with a zero-interest rate. Hence, the calculation is based on the annual average cost. It is observed from the numerical illustration of the model that the optimal life of a vehicle can be determined by comparing the increased running cost to the decreased depreciation value. The two models presented in this article have a computational advantage over existing ones in terms of assisting policy makers to determine vehicles’ optimal replacement policy. The policies include deciding which vehicle should be repaired or replaced, thereby averting losses of human and material resources due to accidents.
Diabetes mellitus (DM) is a chronic metabolic disorder characterised by persistent hyperglycemia arising from impaired insulin secretion, action, or both. The condition disrupts carbohydrate, lipid, and protein metabolism, resulting in widespread systemic complications. This study evaluated the proximate and phytochemical composition of Justicia carnea leaves as well as the antioxidant and antihyperglycemic effects of the methanol leaf extract in streptozotocin (STZ)-induced diabetic Wistar rats. Proximate and phytochemical analyses were conducted using standard procedures. For the in vivo study, thirty-six male Wistar rats (180 – 200 g) were randomly assigned to six groups. Group 1 served as the normal control, Group 2 was diabetic and untreated, Group 3 received metformin (50 mg/kg body weight (bw), while Groups 4 to 6 received 100, 200, and 500 mg/kg bw of the methanol extract, respectively. Diabetes was induced using a single intraperitoneal injection of STZ (50 mg/kg bw). After 21 days of treatment, animals were euthanised to measure antioxidant enzyme activity in the pancreas, liver, and kidney. Phytochemical screening indicated the presence of flavonoids, tannins, steroids, phenols, and terpenoids. Proximate analysis revealed high carbohydrate (47.88%) and moisture (22.12%) contents, with low crude fat (0.23%) and protein (1.26%) levels. Untreated diabetic rats exhibited significantly elevated fasting blood glucose and reduced antioxidant enzymes — superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) (p < 0.05). Treatment with J. carnea extract produced a dose-dependent reduction in fasting blood glucose and significant restoration of antioxidant enzyme activities (p < 0.05). These findings demonstrate that Justicia carnea leaves possess valuable nutritional and bioactive constituents and exhibit strong antioxidant potential, supporting their traditional use and suggesting therapeutic relevance in managing oxidative stress – associated diabetic complications.
In marketing research, the understanding of relationships between variables by statistically controlling for extraneous sources of variation is refined by eliminating covariates. This work examines and eliminates the covariate effect on the sales of grand cereals oil. The data set for the work was on yearly sales (in millions of Naira) of grand cereals oil, Managers’ Age, Gender, and Operating Cost (the covariate) for a period of thirty (30) years (1991 - 2020). A general linear model (GLM) was first fitted to the sales data without the covariate. Then, another GLM with the covariate included (analysis of covariance (ANCOVA)) was fitted. Then, the proportion of total variability in the data accounted for by the covariate alone and by both the dummy variable and the covariate was investigated. The GLM result shows a highly significant effect of both the gender and age, with P< 0.0001, R2 of 49.8%, and mean squared error (MSE) of 70.782. The ANCOVA model showed a highly significant age effect with P< 0.0001, R2 of 80.5%, and a MSE of 27.028, indicating a sharp increase in the power of the test. The study has established the potential of the ANCOVA technique in controlling and eliminating the effect of the concomitant variable.
