Adama University

About: Adama University is a education organization based out in Nazrēt, Ethiopia. It is known for research contribution in the topics: Population & Adsorption. The organization has 840 authors who have published 1010 publications receiving 5547 citations. The organization is also known as: Adama Science and Technology University & ቴክኖሎጂ ዩኒቨርሲቲ, አዳማ ሳይንስና ቴክኖሎጂ ዩኒቨርሲቲ.

DFD-Net: lung cancer detection from denoised CT scan image using deep learning

Abstract: The availability of pulmonary nodules in CT scan image of lung does not completely specify cancer. The noise in an image and morphology of nodules, like shape and size has an implicit and complex association with cancer, and thus, a careful analysis should be mandatory on every suspected nodules and the combination of information of every nodule. In this paper, we introduce a “denoising first” two-path convolutional neural network (DFD-Net) to address this complexity. The introduced model is composed of denoising and detection part in an end to end manner. First, a residual learning denoising model (DR-Net) is employed to remove noise during the preprocessing stage. Then, a two-path convolutional neural network which takes the denoised image by DR-Net as an input to detect lung cancer is employed. The two paths focus on the joint integration of local and global features. To this end, each path employs different receptive field size which aids to model local and global dependencies. To further polish our model performance, in different way from the conventional feature concatenation approaches which directly concatenate two sets of features from different CNN layers, we introduce discriminant correlation analysis to concatenate more representative features. Finally, we also propose a retraining technique that allows us to overcome difficulties associated to the image labels imbalance. We found that this type of model easily first reduce noise in an image, balances the receptive field size effect, affords more representative features, and easily adaptable to the inconsistency among nodule shape and size. Our intensive experimental results achieved competitive results.

Comparison of cryptococcal antigenemia between antiretroviral naïve and antiretroviral experienced HIV positive patients at two hospitals in Ethiopia.

Abstract: Background: Cryptococcal meningitis is a major cause of HIV/AIDS-related deaths in Africa. Cryptococcosis is a neglected killer. However, meningitis can be prevented by early cryptococcal antigen (CrAg) screening and preemptive antifungal treatment during a prolonged period of detectable, subclinical infection. We determined the prevalence of cryptococcal antigenemia in comparison to CD4 count and clinical symptoms. Methods: We surveyed 254 consenting HIV-infected participants to obtain demographic information and clinical history. Serum CrAg was measured by latex agglutination at two sites in the Oromia region of Ethiopia among all persons receiving a CD4 count.

Groundwater Quality Assessment Using Geospatial Techniques and WQI in North East of Adama Town, Oromia Region, Ethiopia

Abstract: Assessment of groundwater quality is vital for the sustainable use of the resources for domestic and agricultural purposes. In this study spatial variation of physicochemical parameters were analyzed for Northeast Adama Town. Water Quality Index (WQI) and irrigation indices were used to determine the suitability of groundwater for drinking and irrigation purposes, respectively. Further, the physical-chemical results were compared with the Ethiopian standards and the World Health Organization (WHO) standards for drinking and public health. Using GIS interpolation methods in Arc GIS 10.3.1, spatial distribution maps of pH, TDS, EC, Cl, HCO3 , SO4 , Ca, Mg, Na and K, RSC, SAR, Na% were prepared. Results indicated that except ASTU well 2, all samples are below the desirable limits of WHO. The WQI results indicated that 85% of samples and 15% of samples were in good and poor categories, respectively. Irrigation indices show that the most groundwater samples have excellent water classes, indicating that they are suitable for irrigation purposes. © 2019 GATHA COGNITION All rights reserved. Article history Received: 11 November 2019 Revised: 25 December 2019 Accepted: 27 December 2019

Groundwater Pollution and Human Health Risks in an Industrialized Region of Southern India: Impacts of the COVID-19 Lockdown and the Monsoon Seasonal Cycles.

Abstract: Samples of groundwater were collected during a post-monsoon period (January) and a pre-monsoon period (May) in 2020 from 30 locations in the rapidly developing industrial and residential area of the Coimbatore region in southern India. These sampling periods coincided with times before and during the lockdown in industrial activity and reduced agricultural activity that occurred in the region due to the COVID-19 pandemic. This provided a unique opportunity to evaluate the effects of reduced anthropogenic activity on groundwater quality. Approximately 17% of the wells affected by high fluoride concentrations in the post-monsoon period returned to levels suitable for human consumption in samples collected in the pre-monsoon period. This was probably due to ion exchange processes, infiltration of rainwater during the seasonal monsoon that diluted concentrations of ions including geogenic fluoride, as well as a reduction in anthropogenic inputs during the lockdown. The total hazard index for fluoride in the post-monsoon samples calculated for children, adult women, and adult men indicated that 73%, 60%, and 50% of the groundwater samples, respectively, had fluoride levels higher than the permissible limit. In this study, nitrate pollution declined by 33.4% by the pre-monsoon period relative to the post-monsoon period. The chemical facies of groundwater reverted from the Na-HCO3-Cl and Na-Cl to the Ca-HCO3 type in pre-monsoon samples. Various geogenic indicators like molar ratios, inter-ionic relations along with graphical tools demonstrated that plagioclase mineral weathering, carbonate dissolution, reverse ion exchange, and anthropogenic inputs are influencing the groundwater chemistry of this region. These findings were further supported by the saturation index assessed for the post- and pre-monsoon samples. COVID-19 lockdown considerably reduced groundwater pollution by Na+, K+, Cl-, NO3¯, and F- ions due to shutdown of industries and reduced agricultural activities. Further groundwater quality improvement during lockdown period there is evidence that the COVID-19 lockdown by increased HCO3¯ ion concentration. Overall results illustrate the positive benefits to groundwater quality that could occur as a result of measures to control anthropogenic inputs of pollutants.