64 research outputs found
Conservation tillage systems and water productivity implications for smallholder farmers in semi-arid Ethiopia
No full textConservation tillage systems have been adopted by farmers in many countries to solve the problem of land degradation and declining water productivity. However, direct application of such tillage systems was not possible among resource poor smallholder farmers in semi arid areas of Ethiopia. Problems such as shortage of rainfall, cost of herbicides, cost of implements and the small seeded crop, tef, which can not be planted in rows required development of locally adapted conservation tillage systems. This book presents the problems of traditional tillage systems and the results of tests carried out on appropriate conservation tillage implements and systems for smallholder farmers in semi arid regions of Ethiopia. The traditional tillage implement, the Maresha Plow and the related tillage systems were identified to be the main causes of repeated and cross plowing that led to land degradation and reduced water productivity. The Maresha modified implements were found to be suitable to undertake conservation tillage systems while being simple, light and affordable. Two types of tillage systems developed for maize and tef were found to reduce surface runoff, increase availability of water to crops and increase yields. The way forward and recommended areas of future research are also presented. More information: http://www.taylorandfrancis.co.ukCivil Engineering and Geoscience
Chronically retained gauze (gossypiboma) resembling a mature cystic teratoma after Cesarean delivery: a case report
No full textAbstract Background A foreign body left behind during an operation is a medico-legal issue. It is an infrequent but avoidable surgical complication, which must be kept in mind in any postoperative patient who presents with pain, infection, or palpable mass. Case summary The author presents a rare case of chronic gossypiboma following a Cesarean delivery in a 40-year-old woman, who was a Para III patient from Western Ethiopia. She had been experiencing dull, aching pain since her previous Cesarean section four years prior. To address her complaints, she visited multiple health facilities where she was prescribed pain relief medications and antibiotics. The patient was eventually taken to the operating room with a preliminary diagnosis of a mature cystic teratoma. However, during laparotomy, surgical gauze was discovered and successfully removed. Conclusion In patients who have previously undergone surgery for obstetric or other gynecological procedures and present with vague abdominal complaints, it is important to consider the possibility of a chronic gossypiboma mimicking a mass of unknown origin. Following established surgical protocols and implementing new preventive measures, such as using tagged gauze/ radio-opaque markers, and ongoing staff training could help reduce or prevent the occurrence gossypiboma. Additionally, the author advises performing delicate surgical procedures to remove retained gauze to prevent bleeding and tissue damage. The gauze should be gently lifted, and the wound must be examined for any damage
Cotton-textile-apparel sectors of India:
Full text link"Cotton, textiles, and apparel are critical agricultural and industrial sectors in India. This study provides descriptions of these sectors and examines the key developments emerging domestically and internationally that affect the challenges and opportunities the sectors face. More than four million farm households produce cotton in India, and about one-quarter of output is produced by marginal and small farms. Although production has expanded—most recently with the introduction of Bt (Bacillus thuringiensis) cotton—domestic prices dropped sharply in the late 1990s, in parallel to world cotton prices. Using partial equilibrium simulations, we estimate that a price movement of the magnitude that occurred has a significant effect on levels of poverty among cotton-producing households. The fiber-to-fabric production chain, from cotton processing through apparel, employs more than 12 million workers in India and provides 16 percent of export earnings. Except for the spinning industry, these sectors are dominated by small, fragmented, and nonintegrated units, which adversely affect their competitiveness. Recent policy reforms have induced some technological improvements. In terms of future prospects for the Indian processing, textile, and apparel industries, our analysis emphasizes three dimensions of reform—the need for further investments in human resource development to improve industry productivity and reduce poverty among workers in these sectors, the emergence of modern domestic retail marketing chains, and the potentially vibrant prospects for the industry that arise from a growing domestic fabric demand and new opportunities in world markets if appropriate policies and investments are undertaken." from authors' abstractCotton, textiles, Apparel, Rural poverty, subsidies, Industry policy, World markets,
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Iron Smelting in Wollega, Ethiopia
No full textThe author is a graduate student affiliated with Addis Ababa University and the University of Bergen, who is currently concentrating on ethnoarchaeological studies in Ethiopia. He has carried out ethnographic field work on iron smelting traditions in West Ethiopia among the Oromo. Mr. Burka has also worked on reconstructing iron smelting techniques and traditions that had a long heritage in that region but declined from regular use over four decades ago. In this field report, he describes his direct observations of methods and traditions of ore mining and treatment, charcoal making, clay extraction, tuyere making, furnace construction, and smelting. This ethnoarchaeological study should provide highly valuable data for other researchers to use in formulating ethnographic analogies for use in archaeological investigations of iron production activities at other sites in Africa and the Americas
Comparative studies between difference and differential equations with emphasis on logistic model, 2016
No full textThis study compares the behavior of differential equations and difference equations of various orders in order to predict the state of the systems at a given time by using initial information about the system. We have demonstrated that differential equations are used in a continuous domain whereas difference equations are employed for discrete dynamical systems. Furthermore, the difference between the two models is amplified in logistic models which both are known to give explicit solutions. However, the discrete logistic model is especially superior in exhibiting a chaotic behavior of the system which the differential equation is incapable of dealing with. The conclusions drawn from the findings conform the similarities and the stark differences between these two models
Consideration of Inter-laminar Strain-energy Continuity in Composite Plate Analysis using Improved Higher-order Theory
Full text linkThe main goal of this paper is to suggest an improved higher-order refined theory for analysing perfectly bonded stacked composite laminates with the usual lamination configurations. The analysis incorporates continuous flexural and in-plane displacements at the interfaces. Furthermore, the transverse shear stress is continuous and constrained with the Lagrange-multiplier technique by introducing 14 new unknown variables that are expressed in terms of the interfacial strain energy, which is assuming to be continuous throughout the thickness of the laminate. To determine the newly introduced flexural and in-plane unknown variables, the total potential energy is minimised using variational calculus. The numerical results are compared with those from existing reliable published papers. In general, the proposed approach is sufficient for analysing laminate structures with the required accuracy.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author
Applications of game theory, tableau, analytics, and R to fashion design, 2018
Full text linkThis thesis presents various models to the fashion industry to predict the profits for some products. To determine the expected performance of each product in 2016, we used tools of game theory to help us identify the expected value. We went further and performed a simple linear regression and used scatter plots to help us predict further the performance of the products of Prada. We used tools of game theory, analytics, and statistics to help us predict the performance of some of Prada's products. We also used the Tableau platform to visualize an overview of the products' performances. All of these tools were used to aid in finding better predictions of Prada's product performances. KEY TERMS: Game theory, expected value, Pradas products, performance, Fashion Design, prediction, Leather Goods, Footwear, Clothing, "Others", Tableau, and R., Analysis, Applied Statistics, Mathematics, Probability, Statistical Models, Statistics and Probabilit
Methods for Estimating Aboveground Biomass and its Components for Douglas-fir and lodgepole pine trees
Full text linkEstimating aboveground biomass and its components requires sound statistical formulation and evaluation. Using data collected from 55 destructively sampled trees in different parts of Oregon, we evaluated the performance of three groups of methods to estimate total aboveground biomass and/or its components based on the bias and root mean squared error (RMSE) they produced. The first group of methods used analytical approach to estimate total and component biomass using existing equations, and produced biased estimates for our dataset. The second group used a system of equations fitted with seemingly unrelated regression (SUR), and were superior to the group I methods in terms of bias and RMSE. The third group of methods predicted the proportion of biomass in each component using beta, Dirichlet, and multinomial loglinear regression (MLR). The predicted proportions were then applied to the total aboveground biomass to obtain amount of biomass in each component. The MLR approach consistently produced smaller RMSEs compared to both SUR approaches. The beta and Dirichlet regressions were superior to both SUR methods except for Douglas-fir branch biomass for which the simple SUR produced smaller RMSE compared to the beta and Dirichlet regressions.The presentation of the authors' names and (or) special characters in the title of the pdf file of the accepted manuscript may differ slightly from what is displayed on the item page. The information in the pdf file of the accepted manuscript reflects the original submission by the author
Dynamic Bayesian network modeling for longitudinal data on child undernutrition in Ethiopia (2002-2016)
Full text linkAbstract
Introduction:
Dynamic Bayesian networks improve the modeling of complex systems by incorporating continuous probabilistic relationships between covariates that change over time. This study aimed to analyze the complex causal links contributing to child undernutrition using dynamic Bayesian network modeling, examining both the best- and worst-case scenarios. The Young Cohort of the Ethiopian Young Lives dataset from 2002–2016 was used to analyze the complex relationships among various covariates influencing child undernutrition. We used a built-in Bayes server tool to identify potential features, followed by building the structure of the directed acyclic graph using a structural learning algorithm. The maximum posterior is determined using the relevance tree algorithm. The node with the highest values of mutual information and target entropy reduction, along with the lowest value of target entropy, was considered to have the strongest predictive power in the dataset.
Results:
This study revealed that long-term participation in programs increased the likelihood of children being in a normal nutritional state. Key factors influencing the nutritional status of children under two years of age include the mother’s education level, her subjective well-being, and the household’s wealth quintile. Children with educated parents were more likely to have a healthy nutritional status. Additionally, the causal pathway of intervention programs → wealth quintile → child nutritional status consistently exceeded 90% in Waves 3, 4, and 5, indicating a strong relationship. Similarly, the relationship between intervention programs → food security → child nutritional status was nearly perfect at 99.99% in Waves 4 and 5, indicating a strong association. Finally, the study revealed that household participation in intervention programs significantly reduces undernutrition in best-case scenarios, while the absence of support poses a higher risk in worst-case conditions.
Conclusion:
The comprehensive intervention program strongly improved household wealth, food security, and maternal well-being, which in turn affected children’s nutritional status.Abstract
Introduction:
Dynamic Bayesian networks improve the modeling of complex systems by incorporating continuous probabilistic relationships between covariates that change over time. This study aimed to analyze the complex causal links contributing to child undernutrition using dynamic Bayesian network modeling, examining both the best- and worst-case scenarios. The Young Cohort of the Ethiopian Young Lives dataset from 2002–2016 was used to analyze the complex relationships among various covariates influencing child undernutrition. We used a built-in Bayes server tool to identify potential features, followed by building the structure of the directed acyclic graph using a structural learning algorithm. The maximum posterior is determined using the relevance tree algorithm. The node with the highest values of mutual information and target entropy reduction, along with the lowest value of target entropy, was considered to have the strongest predictive power in the dataset.
Results:
This study revealed that long-term participation in programs increased the likelihood of children being in a normal nutritional state. Key factors influencing the nutritional status of children under two years of age include the mother’s education level, her subjective well-being, and the household’s wealth quintile. Children with educated parents were more likely to have a healthy nutritional status. Additionally, the causal pathway of intervention programs → wealth quintile → child nutritional status consistently exceeded 90% in Waves 3, 4, and 5, indicating a strong relationship. Similarly, the relationship between intervention programs → food security → child nutritional status was nearly perfect at 99.99% in Waves 4 and 5, indicating a strong association. Finally, the study revealed that household participation in intervention programs significantly reduces undernutrition in best-case scenarios, while the absence of support poses a higher risk in worst-case conditions.
Conclusion:
The comprehensive intervention program strongly improved household wealth, food security, and maternal well-being, which in turn affected children’s nutritional status
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Evaluation of agronomic performance and grain yield stability of bread wheat (Triticum aestivum) genotypes in East Shewa zone, Oromia
Full text linkA field experiment was conducted at Adami Tulu Agricultural Research Center, as well as in the Lume and Dugda Districts, during the main cropping seasons of 2022 and 2023. The purpose of this study was to identify stable and high yielder bread wheat genotypes in the East Shewa Zone across three distinct districts. These districts exhibit varying environmental conditions and altitudes, with a diversity of soil types characterized by differing compositions. A total of fifteen genotypes were precisely evaluated utilizing a randomized complete block design with three replications. Analysis of variance revealed significant effects of genotype, environment, and their interaction on grain yield. Additive Main Effects and Multiplicative Interaction (AMMI) analysis indicated that the environment significantly influenced yield, accounting for 48.78% of the total variation, followed by genotype (23.89%) and genotype × environment interaction (16.19%). The first two interaction principal components (IPCA-I and IPCA-II) explained 44.6% and 27.7% of the genotype × environment interaction, respectively, and were used to assess stability. Based on stability parameters (ASV and GGE-Biplot) and mean grain yield, genotypes G-6, G-1, and G-5 were identified as stable and high-yielding candidates for potential release. AMMI and GGE-biplot analyses revealed specific adaptation patterns among genotypes, with some performing better in particular environments. These findings highlight the importance of multi-environmental trials for accurate genotype evaluation. Given their yield and stability, genotypes G-6, G-1, and G-5 were promising resources for improving bread wheat productivity in East Shewa Zone and similar agro-ecologies. We recommend further validation trials and farmer participatory evaluations to ensure acceptability and performance under on-farm conditions. Additionally, these superior genotypes could be used as parents in future breeding programs. © 2024 The Author(s
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