College of Natural and Computational Sciences

Permanent URI for this communityhttps://repository.mu.edu.et/handle/123456789/4

Browse

Search Results

Now showing 1 - 10 of 48
  • No Thumbnail Available
    Item
    Quantitative Analysis of Potentially Toxic Elements (Pb, Cd, Co, Cr, Fe, Mn, and Ni) in Lipstick Brands Available in Mekelle Markets, Tigray, Ethiopia
    (Mekelle University, 2025-09-25) Asfaw Mulugeta Gebremedhin
    Lipsticks, widely used cosmetic products, can be a significant source of potentially toxic elements exposure through unintentional ingestion. This poses potential long-term health risks due to the bioaccumulative nature of metals like Pb, Cd, and Cr. This study aimed to quantify the concentrations of seven potentially toxic elements (Pb, Cd, Co, Cr, Fe, Mn, and Ni) in three widely available and commonly sold lipstick brands from local markets in Mekelle, Ethiopia. Samples were prepared using a wet acid digestion method with a concentrated 5:1:1 mixture of HNO3, HCl, and H2O2 and analyzed through Flame Atomic Absorption Spectrophotometer (FAAS). Cd was not detected in any sample. The concentration ranges across all samples in ppm were: Pb (0.0400–0.1000), Co (3.740–5.570), Cr (10.62–18.05), Fe (75.00–1838), Mn (0.1500–0.1600), and Ni (12.83–51.41). The levels of Pb were well below the 10 ppm guidance limit set by international bodies like Health Canada, U.S. Food and Drug Administration (FDA), their consistent presence is a concern. However, concentrations of Cr and Ni, known sensitizers, were notable. As an intentionally added pigment, Fe showed the highest and most variable concentrations. Although the detected levels of toxic metals were within international permissible limits, their consistent presence is a public health concern. Given the direct ingestion route and frequency of application, daily use may contribute to the cumulative body burden of these metals over time. This study, though limited by a small sample size, highlights the urgent need for healthy regulatory oversight and routine quality control of cosmetics in Ethiopia. Further research is essential to assess a wider range of products and evaluate the associated health risks for consumers.
  • No Thumbnail Available
    Item
    The steady-state squeezing and entanglement properties of the cavity radiation from parametric oscillation
    (Mekelle University, 2025-01-29) Shambel Aligaz
    In this thesis, we study the quantum properties of the light generated by a para metric oscillation with the cavity mode driven by coherent light beams coupled to a two-mode squeezed vacuum reservoir. Applying the master equation describing the interaction of the cavity modes with the driving coherent light beams and with the two-mode squeezed vacuum reservoir, we obtain the quantum Langevin equations. The solutions of the resulting equations are then used to calculate the mean and vari ance of the photon number, the quadrature variance, global quadrature squeezing and local quadrature squeezing of two-mode cavity light. It is found that the squeezing occurs in the plus quadrature and the driving coherent light beams have no effect on the squeezing properties of the two-mode cavity light. We have found that, at steady state and at threshold, there is a maximum squeezing of the two-mode cavity light when the cavity is coupled to squeezed vacuum reservoir. In general, the degree of squeezing increases with the squeezed parameter whereas the driving coherent light beams and the squeezing parameter have the effect of increasing the mean photon number of the two-mode cavity light.Contents
  • No Thumbnail Available
    Item
    Muon Pair Production from Electron-Positron and Positronium Annihilation in Polarized Laser Field
    (Mekelle University, 2025-08-22) Seid Yimer Ahmed
    This thesis investigates muon pair production resulting from electron-positron annihilation and positronium interactions within polarized laser fields. The study systematically examines how various parameters of the laser field; specifically polarization, intensity, and photon energy affect the production rates and energy distributions of muon pairs. Through a series of computational simulations and sensitivity analyses, we established that increased laser intensity significantly enhances muon pair production rates, corroborating theoretical predictions from Quantum Electrodynamics (QED). Furthermore, the analysis reveals that circularly polarized light is more effective than linearly polarized light in facilitating muon pair production, underscoring the critical role of polarization in the interaction dynamics. Sensitivity analyses indicate that muon production rates are particularly responsive to changes in laser intensity and polarization, while variations in the initial energies of electron-positron pairs exert a comparatively minor influence. To validate these findings, future work is proposed, which includes experimental studies employing high-intensity laser systems to observe muon pair production under controlled conditions. The exploration of additional parameters, such as the energy distribution of the electron-positron pairs and varying laser wavelengths, is recommended to gain further insights into optimizing muon production. This thesis contributes to the growing body of research in high-energy particle physics, offering valuable insights for future experimental designs and the development of advanced laser systems aimed at enhancing muon production efficiencies.
  • No Thumbnail Available
    Item
    Investigating the Effects of GeoGebra on University Mathematics Teachers‘ Perceptions, Beliefs, Skills and Achievements in Matrices and Calculus-I: The Case of Northern Ethiopian Universities
    (Mekelle University, 2025-05-15) Gebreslassie Tesfay Berhe
    The integration of dynamic mathematical software into HE has the potential to transform traditional mathematics education. Among such tools GeoGebra offers a unique opportunity for visualizing abstract concepts in matrices and calculus-I. This study aimed to explore how University Mathematics Teachers (UMTs) in Ethiopia use the open-source software-GeoGebra into their teaching practices. It identifies the barriers that UMTs face when using GeoGebra and examines their perceptions, beliefs, skills, and frequency of use. Furthermore, the study assessed the impact of GeoGebra training on UMTs' achievement in matrices and Calculus-I, and extent of GeoGebra use. A quasi-experimental, mixed methods design involving 96 participants using surveys, interviews, and pre-and post-tests. The survey participants were selected using a convenience sampling method (considering universities in the Northern Ethiopia; Tigray), while interviewees were chosen through purposive sampling. A training intervention on GeoGebra was provided to UMTs, supplemented by semi-structured and follow-up interviews to collect comprehensive data. The quantitative data were analyzed through descriptive and inferential statistics, including correlation analysis, One-way ANOVA, ANCOVA, independent samples t-tests, dependent paired samples t-tests, and logistic and linear regression analyses using SPSS-20; and the qualitative data using text thematic analysis. Analysis of responses indicated that UMTs encounter challenges in utilizing GeoGebra in their teaching due to students' familiarity with the software, insufficient access and support for technology, UMTs' perceptions, beliefs, and skills, lack of funding, inadequate staff support, insufficient training, awareness and exposure to mathematical software, rigid mathematics curriculum, UMTs‘ resistance to change, and infrastructural shortcomings. Despite these challenges, UMTs exhibited high perceptions and beliefs about GeoGebra, moderate skills in using it, and low levels of actual implementation in their teaching practices. The Findings indicated there is a significant positive relationship between UMTs‘ extent of GeoGebra use and their perceptions, beliefs, and skills regarding the software. The results of the one-way ANOVA indicated that there were no significant differences in the mean scores for matrices and Calculus I achievements before the intervention. However, the post-intervention analysis revealed significant gains in UMTs‘perception, beliefs, skills, and academic achievement) (eta squared = 0.941) with GeoGebra integration accounting for 49.1% of score variation. A post hoc analysis using Fisher's Least Significant Difference (LSD) method also revealed significant differences among certain pairs of tests, thereby confirming that the GeoGebra training intervention had a substantial positive effect on UMTs' achievements in both matrices and Calculus-I. After controlling for covariates, it was found that U2 had a significantly higher mean score than both U1 and U3; and the GeoGebra training intervention accounted for 22.1% of the variability in UMTs' posttest achievements in matrices and Calculus-I. Additionally, the linear regression analysis revealed that UMTs‘ skills in utilizing GeoGebra significantly predict their extent of GeoGebra usage in their teaching practices. Notably, factors such as gender, highest academic qualification, and academic rank also significantly influence UMTs' usage of GeoGebra in their mathematics instruction when all their backgrounds were considered. While in Post-intervention, there were no significant differences among the UMTs across the three universities; all groups exhibited positive mean gains in their beliefs, perceptions, skills in using, and the extent of utilizing GeoGebra in their mathematics teaching practices. Statistically significant differences were observed regarding UMTs' perceptions, beliefs, skills, and usage of GeoGebra before and after the training intervention. Finally, this study provides valuable insights for policy developers and curriculum designers about the challenges faced by UMTs in tertiary education. The findings also prompt further research into the effectiveness of GeoGebra training and its integration into higher education institutions (HEIs) as a foundational support for teaching mathematics. Moreover, mathematics educators and researchers are encouraged to investigate the impact of GeoGebra training on students' mathematical concepts understanding to devise effective pedagogical strategies.
  • No Thumbnail Available
    Item
    SURVIVAL ANALYSIS FOR HIV-TB CO-INFECTED PATIENTS UNDER ANTIRETROVIRAL THERAPY IN MEKELLE HOSPITAL AND AYDER COMPREHENSIVE REFERAL HOSPITAL TIGRAY, ETHIOPIA: APPLICATIONS OF A PARAMETRIC SHARED FRAILTY MODEL
    (Mekelle University, 2024-11-28) Tekleweyni Haftu
    Background: Human immunodeficiency virus (HIV) is an infection that attacks the body’s immune system. Acquired immunodeficiency syndrome (AIDS) is the most advanced stage of the disease. HIV remains one of the world's most significant public health challenges, particularly in low- and middle-income countries. Objectives: This study aimed to determine the potential risk factors affecting the time-to-death of HIV-TB co-infected patients in Mekelle and Ayder Comprehensive Referral hospitals and also demonstrate the application of parametric survival models in analyzing these survival outcomes. Methods: Parametric shared frailty models have been used with four baseline hazard functions (Exponential, Weibull, Log-logistic, Log-normal) and two frailty distributions (Gamma, InverseGaussian). 215 HIV-TB co-infected patients whose age was 18 and above who started ART from January 2015 to December 2016 and followed up to January 2020 were included in the study from Mekelle and Ayder hospitals. Data were analyzed using statistical software R version 4.4.1 and STATA version 14.0. Results: Out of 215 patients, about 60(28%) died while 155(72%) were censored during the follow-up period with the median death time of HIV-TB co-infected patients at 30 months. The clustering effect was significant, and the Weibull-Inverse Gaussian shared frailty model was preferred over the rest parametric shared frailty models based on the Akaike Information Criterion (AIC) and Bayesian Information Criteria (BIC). The result shows patients’ educational level, baseline Weight, TB type, baseline CD4, and place of residence were significant, whereas sex, WHO clinical stage, marital status, functional status, regimen type, and age were not significant covariates for HIV-TB co-infected patients in Mekelle and Ayder comprehensive Referral hospitals. The clustering effect was significant for modeling the time-to-death of HIV-TB patients’ dataset and there was heterogeneity among the hospitals on the death of patients (θ=040.). Conclusion: This study showed that there was a clustering (frailty) effect on modeling time to Death among patients treated in Mekelle and Ayder comprehensive hospitals because of heterogeneity in hospitals from which the patients are treated, assuming patients treated in the same hospital share similar risk factors related to death.
  • No Thumbnail Available
    Item
    Analysis of Multi-environmental Trial Data Using AMMI and GGE Biplot on Barley Genotypes Evaluated in Tigray
    (Mekelle University, 2023-11-08) Tamrat Berhe
    Barley (Hordeum vulgare L.) was one of the first plants people grew for food, and now it's grown all over the world and it has a special role in Ethiopian agriculture. However, production is affected by environment interaction and lack of stable genotypes across locations. The presence of genotype-environment interaction (GEI) influences production making the selection of cultivars in a complex process. Since, this experiment were conducted for forty barley genotypes by Alpha lattice design using two replications at three locations in Tigray during 2017 and 2018 cropping seasons considering each year-location combination as a different environments. The study carried out with objectives to estimate magnitude of genotype by environment interaction, comparing AMMI and GGE to evaluate stability of genotypes and identifying superior genotypes. We observed significance effects in all sources of combined ANOVA, since the grain yields of all 40 barley genotypes were significantly affected by environment, which accounted for 40.6 % of the total variation, whereas genotype and genotypeenvironment interaction accounted for 21.12 % and 23.07 %, respectively. The two most used methods to analyze GEI and evaluate genotypes are AMMI and GGE Biplot, being used for the analysis of multi environment trials data (MET).Both models were equivalent for the data’s evaluation, but GGE permitting increased reliability in the selection of superior cultivars (Which-won-where pattern) and test environments (discrimitiveness vs. representativeness).Wricke’s ecovalence, Finley-Wilkinson, Shukla’s stability, Lin&Binns cultivar superiority measure, AMMI Stability Value (ASV), and YSI stability analysis measures also used to identify stable genotypes, and G19, G36, G5 are the most stable genotypes in almost the stability analysis measures, since they are superior genotypes with all test environments. While the genotypes G33, G32, G12 and G18 also the instable genotypes in the test environments. GGE Biplot view of relation among test environments of this study showed that; Among the testing environments Hagereselam 2018 is an ideal testing location to identify stable and high yielding genotypes followed by Ayba 2018, since Hagereselam 2018 and Ayba 2018 are most applicable test locations for identifying stable and high yielding barley genotypes for the region. Mean performance and stability of GGE biplot indicated that G24 had the ideal genotype with highest mean yield as well as stability with desirable genotypes G20, G19, G5, G36, while G33 and G30 had the lowest mean yield and less stability genotypes in all the six test environments.
  • No Thumbnail Available
    Item
    SPATIAL DISTRIBUTION AND DETERMINANTS OF ANAEMIA AMONG WOMEN OF REPRODUCTIVE AGE IN ETHIOPIA USING MIXED-EFFECT ORDINAL LOGISTIC REGRESSION MODEL
    (Mekelle University, 2024-12-28) Solomon Tekeste
    Background: Anaemia is a condition characterized by a low blood hemoglobin concentration (120 g/L in non-pregnant women and below 110 g/L in pregnant women). It primarily affects women of reproductive age (WRA) and who suffer from anaemia has experienced detrimental effects on their mental development and future social functioning. Objectives: This study aimed to assess the spatial distribution and determinants of anaemia among women of reproductive age in Ethiopia. Methods: The study participants were all the WRA who were confirmed to anaemia from the 2019 EMDHS data source. The survey considered 8885 WRA; of which 1483 severe, 534 moderate, 1778 mild and 5090 none anaemia levels were included in this study. The study variable was defined as the ordinal level of anaemia (none, mild, moderate and severe) based on the WHO cut-off points. In this study, Moran’s-I, was used to investigate the presence of spatial autocorrelation. A mixed effect ordinal logistic regression model used allowed to analyze random and fixed effects of some covariates, spatial effects, and other fixed covariates. Inference used a full GLMM and several methods can be used to assess the goodness of fit in GLMMs, including the AIC and BIC techniques. Results: Out of 8885 WRA; included in this study 1483(16.7%) were found at a severe level of anemic. Due to the BIC model selection criteria, the GLMM model was found to be appropriate. From the model Individual factors (age group, religion, wealth index and marital status) and community factors (cooking fuel type, number of children, access to electricity, and having refrigerators) are found to be determinants, significant determinants of anaemia status among WRA and the spatial analysis demonstrated a clustered pattern of anaemia distribution, confirmed by the global Moran's I statistic (0.146652, p-value < 0.001). Conclusion: The finding revealed a spatial variation of anaemia status among WRA across the regions of Ethiopia with higher prevalence in the eastern parts of the country specifically in Somali and Harari regions. The application of the GLMM provided a more detailed understanding of the factors influencing anaemia status.
  • No Thumbnail Available
    Item
    Statistical Analysis of Multi Environment Trials on Durum Wheat: The Use of AMMI and Stability Indices to Model Genotype by Environment Interaction
    (Mekelle University, 2023-11-28) Shshaye Hailu
    Background: Durum wheat is one of the most important crops worldwide with an annual production of 37 million tons and Ethiopia is the major durum wheat producer in Sub-Saharan Africa (SSA). Crop breeders have worked to create genotypes with improved grain production, quality, and other desirable qualities under a variety of diverse environmental situations. Genotype × environment (G×E) interaction is one of the main complications in the selection of broad adaptation in most breeding programs. Objective: The goal of the study was to assess genotype by environment interaction in multienvironment trials and identify stable and adaptive durum wheat varieties using AMMI and stability measures. Method: The experiment was conducted at Beati-Maymesanu in Ganta-Afeshum Woreda, Agarba in Degua Tembein Woreda, Atsela in Emba Alajie Woreda, and Zata in Ofla Woreda during in 2015 and 2016 under Production and contrasting growing conditions. Thirty six durum wheat varieties were released using Simple Alpha Lattice design with two replications. This study was used AMMI and stability measures for assessing among environments and genotypes. Result: The Combined analysis of variance revealed highly significant difference among genotypes, environments and GEI for durum wheat. Stability analysis of grain yield was executed using environmental variance, shukla‟s stability, Wricks‟ ecovalence and AMMI stability value (ASV). The analysis of variance for the AMMI model were highly significant variation differences between genotypes, environments and the interaction effect of G x E. The first two interaction principal component axes (IPCA) of the AMMI model accounted for 48.73% of the total G x E interaction sum of squares for grain yield. Conclusion and Recommendation: According to the AMMI biplot analysis, Genotypes G30 (55D3), G11 (248478) and G25 (236295) were more stable, while, G33 (222415) and G21 (8436) are the unstable genotypes and E5 (Beati-Maymesanu-2016) was the highest yielding environment while, E8 (Zata-2016) was the low yielding among eight environments. Keywords: AMMI, Genotype by Environment interaction
  • No Thumbnail Available
    Item
    Prevalence & Risk factors of Patent Ductus Arteriosus (PDA) in Preterm Neonates: Evidence from Survival & Shared Frailty Model
    (Mekelle University, 2023-11-28) Nigus Gebreab
    Background: The ductus arteriosus is a leftover fetal artery connecting the main body artery (aorta) and the main lung artery (pulmonary artery). The ductus allows blood to detour away from the lungs before birth. Every baby is born with a ductus arteriosus. After birth, the opening is no longer needed and it usually narrows and closes within the first few days. Patent ductus arteriosus (PDA), resulted when this artery remains open (patent) after birth, is a heart problem that occurs soon after birth in some babies. Its human and economic loss is too much in general if it is not treated at all or treated early. Objective: The overall objective of this study was to assess prevalence of PDA in preterm neonates; their survival time (time to death) & associate risk factors. Methods: To address the study objective, a secondary data from Health Facilities of Mekelle City was collected from 125 preterm neonates who initiated their follow up between December 2019 and December 2020. The Cox PH model with parametric shared frailty distribution where hospitals (health facilities) preterm neonates treated used as a clustering effect in the models. The gamma and inverse Gaussian shared frailty distributions with Exponential, Weibull and log-logistic baseline models was employed to analyze risk factors associated with age at circumcision using socio-economic and demographic factors. All the fitted models were compared by using AIC and BIC values from actual dataset. Results: A total of 125 children were seen at the Health Facilities of Mekelle City during the study period. The result revealed that about 20% of preterm neonates were exposed to PDA while the remaining were not. The AIC value for the three baseline distributions (Exponential, Weibull, and Gompertz) of PH model was found 173.6275, 174.6895, and 175.6086 and the BIC value of those baseline distributions for the same model was also found 216.0522, 219.9425, and 220.8616 respectively. The AIC value for the three baseline distributions for gamma shared frailty model was found 172.5497, 176.6895, and 176.6896 (the same value with Weibull) and BIC value of those baseline distributions for the same model also found 220.8805, 224.7708, and 224.7708 (the same with Weibull) respectively. Based on AIC and BIC values from simulation experiment and graphical evidences, Gamma shared frailty model, with the exponential baseline preferred when compared with other models. The clustering effect (the hospital effect) was significant for modeling the determinants of time-to-death preterm neonates with PDA. The estimated value of ix | P a g e theta (θ) which is a measure of contribution of a frailty component to the model was 1.1056 and a chi-square value of 0.003722 with one degree of freedom resulted a p-value of 0.0027. Based on the result of Gamma shared frailty model with the exponential baseline, gestational age, birth weight, place of delivery at home, maternal history with HIV, and treatment with paracetamol were found to be the most significant risk factors of the outcome variable, survival time (time to death from PDA). The hazard ratio and 95% Confidence interval of gestational age and birth weight was also 2.0742 with CI (0.5905259, 0.9013781) and 2.7191 with CI (1.000007, 1.000614) that yielded a p-value of 0.003 and 0.045 respectively. The hazard ratio and 95% CI for the covariates place of delivery at home, maternal history with HIV, and treatment with paracetamol were 5.1852 with CI (0.7416363, 5.1268725), 2.139 and (2.417719, 263.6325), and 42.0056 with (-3881.608, 3846.564) which yielded a p-value of 0.0092, and 0.007 respectively. They have also a prevalence rate of a unit (for place of delivery at home and maternal history with HIV) and 0.13 for treatment with paracetamol (No). The overall prevalence rate was also yielded 0.32. Conclusions: The model suggested that there is a strong evidence of heterogeneity among health facilities where the preterm neonates were treated. From the candidate models, Gamma shared frailty model, with the exponential baseline was an appropriate model for predicting the PDA data. There was a frailty effect on the survival of the preterm neonates that arises due to differences in the distribution of hospitals of the neonates. The risk factors place of delivery at home, maternal history with HIV, gestational age (week), Birth weight, and treatment with paracetamol were statistically significant for the survival of preterm neonates whereas the other risk factors were not statistically significant. The frailty component had also a significant effect to the model
  • No Thumbnail Available
    Item
    Bayesian Survival Analysis of Adult Tuberculosis Patients: the Case of Lemlem Karl Hospital, Maichew, Southern Tigray.
    (Mekelle University, 2024-11-28) Lemlem Tekle
    Tuberculosis is an airborne disease caused by the bacterium Mycobacterium tuberculosis, primarily affects the lungs. Transmission occurs through the air when individuals with pulmonary TB are not undergoing proper treatment. This study aimed to identify factors affecting the survival time of adult TB patients in LKH, Maichew, and Southern Tigray. To address the objective of this study, 242 adult TB patients were included in the study based on data taken from the medical records of patients enrolled from July; 2020 to January; 2024. Almost half, 50.4%, of the adult TB patients were female. Kaplan Meier plots were used for comparison of survival function; Bayesian survival models were used to identify factors affecting the survival time of adult TB patients. Of the total patients in the study 178 (73.6%) were censored. The estimated median survival time of patients was 26 months. Bayesian log-normal accelerated failure time model using MCMC and INLA method fit adult TB data better than other Bayesian accelerated failure time models used in this study. The Bayesian log-normal accelerated failure time model using the INLA method was preferable to the MCMC method due to smaller standard error and narrow credible interval. The results of this model show that the survival time of adult TB patients is significantly affected by age, residence, body weight, HIV status, BMI, dose level and cigarette smoking of adult TB patients(pvalue<0.05). Bayesian log-normal accelerated failure time model using the INLA method describes the adult TB dataset well. From the Bayesian result, the risk factors for the survival time of adult TB patients were age group (31 to 45, 𝛾 = 0.8607),(46 to 60, 𝛾 = 0.7189)and( >60, 𝛾 = 0.6637);residence(rural,𝛾 =0.7408); HIV (Positives, 𝛾 = 0.68386); Dose (III, 𝛾 = 0.6570) ,IV 𝛾 = 0.9512),BMI(Overweight, 𝛾 = 0.8607) and (Obese 𝛾 = 0.0779); base line weight(> 50kg, 𝛾 = 0.8693) and (smokers, 𝛾 = 0.8607) at 95% credible interval and those factors were prolonged the timing death of adult TB patients. Therefore, health professionals should focus on the identified factors to improve the survival time of TB patients.