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Application of Water Quality Model QUAL2K to Model the Dispersion of Pollutants in River Ndarugu, Kenya

Computational Water, Energy, and Environmental Engineering 2014年第4期3卷 162-169页

作者： Letensie Tseggai Hadgu Maurice Omondi Nyadawa john kimani mwangi Purity Muthoni Kibetu Beraki Bahre Mehari Department of Civil Construction and Environmental Engineering Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya Jaramogi Oginga Odinga University of Science and Technology Bondo Kenya

Ndarugu River, Kenya, during its course through the different agricultural and industrial areas of Gatundu, Gachororo and Juja farms, receives untreated industrial, domestic and agricultural waste of point source discharges from coffee and tea factories. During wet season the water is also polluted by non-point (diffuse) sources created by runoff carrying soil, fertilizer and pesticide residues from the catchment area. This study involved the calibration of water quality model QUAL2K to predict the water quality of this segment of the river. The model was calibrated and validated for flow discharge (Q), temperature (T°), flow velocity (V), biochemical oxygen demand (BOD5), dissolved oxygen (DO) and nitrate (NO3-N), using data collected and analyzed during field and laboratory measurements done in July and November-December 2013. The model was then used in simulation and its performance was evaluated using statistical criteria based on correlation coefficient (R2) and standard errors (SE) between the observed and simulated data. The model reflected the field data quite well with minor exceptions. In spite of these minor differences between the measured and simulated data set at some points, the calibration and validation results are acceptable especially for developing countries where the financial resources for frequent monitoring works and higher accuracy data analysis are very limited. The water is being polluted by the human activities in the catchment. There is need for proper control of wastewater by various techniques, and preliminary treatment of waste discharges prior to effluent disposal. Management of the watershed is necessary so as to protect the river from the adverse impacts of agricultural activities and save it from further deterioration.

关键词： BOD5 DO QUAL2K River Pollution Water Quality Modeling

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Bacterial Sample Concentration and Culture Monitoring Using a PEG-Based Osmotic System with Inline Impedance and Voltammetry Measurements

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Journal of Analysis and Testing 2019年第2期3卷 166-174页

作者： Martin K.kimani john mwangi Edgar D.Goluch Department of Chemical Engineering Northeastern UniversityBostonMA 02115USA Department of Bioengineering Northeastern UniversityBostonMA 02115USA

Impedance measurements using graphite electrodes were used to detect the increase in culture medium conductivity due to bacteria growth in real time along with simultaneous voltammetric monitoring of pyocyanin *** methods were compared to conventional continuous monitoring of bacterial cultures using turbidity measurement at an optical density of 600 nm(OD600).A practical osmotic system was further designed for concentrating bacterial cultures during growth to enable earlier detection using the electrochemical *** cultures,starting from an initial culture density of 1×10^(8) cells/mL,were grown inside a sealed cellulose ester dialysis membrane,while polyethylene glycol in LB medium was used as the draw solution outside the membrane to gradually concentrate the growing cultures.0.7-mm-diameter graphite for mechanical pencils was utilized as working and counter electrodes with a platinum wire reference electrode for electrochemical measurements with and without the osmotic *** the absence of forward osmosis,impedance meas-urements detected culture growth~1 h faster than conventional *** osmosis showed a twofold decrease in the time to detect pyocyanin production as an indicator for bacterial *** impedance monitoring,removal of water by osmosis was conflated with the impedance decrease due to cell growth;however,the results show a promising ability to detect bacteria growth via an observed shift in osmotic impedance profile when bacteria are present in a *** monitoring the deviation in the impedance profile,a threefold improvement in detection time was achieved when compared to conventional OD600 measurements.

关键词： Osmotic concentration Pseudomonas aeruginosa Bacterial growth detection Impedance electrochemical monitoring Forward osmosis

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Mixture Ratio Estimators Using Multi-Auxiliary Variables and Attributes for Two-Phase Sampling

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Open Journal of Statistics 2014年第9期4卷 776-788页

作者： Paul mwangi Waweru john Kung’u James Kahiri Department of Statistics and Actuarial Science Kenyatta University Nairobi Kenya

In this paper, we have proposed three classes of mixture ratio estimators for estimating population mean by using information on auxiliary variables and attributes simultaneously in two-phase sampling under full, partial and no information cases and analyzed the properties of the estimators. A simulated study was carried out to compare the performance of the proposed estimators with the existing estimators of finite population mean. It has been found that the mixture ratio estimator in full information case using multiple auxiliary variables and attributes is more efficient than mean per unit, ratio estimator using one auxiliary variable and one attribute, ratio estimator using multiple auxiliary variable and multiple auxiliary attributes and mixture ratio estimators in both partial and no information case in two-phase sampling. A mixture ratio estimator in partial information case is more efficient than mixture ratio estimators in no information case.

关键词： Ratio Estimator Multiple Auxiliary Variables Multiple Auxiliary Attributes Two-Phase Sampling Bi-Serial Correlation Coefficient

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Enhancing Pneumonia Detection in Pediatric Chest X-Rays Using CGAN-Augmented Datasets and Lightweight Deep Transfer Learning Models

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Journal of Data Analysis and Information Processing 2024年第1期12卷 1-23页

作者： Coulibaly Mohamed Ronald Waweru mwangi john M. Kihoro Department of Mathematics Pan African University Institute for Basic Sciences Technology and Innovation (PAUSTI) Nairobi Kenya Department of Computing Jomo Kenyatta University of Agriculture and Technology Nairobi Kenya School of Computing and Mathematics The Cooperative University of Kenya Nairobi Kenya

Pneumonia ranks as a leading cause of mortality, particularly in children aged five and under. Detecting this disease typically requires radiologists to examine chest X-rays and report their findings to physicians, a task susceptible to human error. The application of Deep Transfer Learning (DTL) for the identification of pneumonia through chest X-rays is hindered by a shortage of available images, which has led to less than optimal DTL performance and issues with overfitting. Overfitting is characterized by a model’s learning that is too closely fitted to the training data, reducing its effectiveness on unseen data. The problem of overfitting is especially prevalent in medical image processing due to the high costs and extensive time required for image annotation, as well as the challenge of collecting substantial datasets that also respect patient privacy concerning infectious diseases such as pneumonia. To mitigate these challenges, this paper introduces the use of conditional generative adversarial networks (CGAN) to enrich the pneumonia dataset with 2690 synthesized X-ray images of the minority class, aiming to even out the dataset distribution for improved diagnostic performance. Subsequently, we applied four modified lightweight deep transfer learning models such as Xception, MobileNetV2, MobileNet, and EfficientNetB0. These models have been fine-tuned and evaluated, demonstrating remarkable detection accuracies of 99.26%, 98.23%, 97.06%, and 94.55%, respectively, across fifty epochs. The experimental results validate that the models we have proposed achieve high detection accuracy rates, with the best model reaching up to 99.26% effectiveness, outperforming other models in the diagnosis of pneumonia from X-ray images.

关键词： Pneumonia Detection Pediatric Radiology CGAN (Conditional Generative Adversarial Networks) Deep Transfer Learning Medical Image Analysis

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基于MaxEnt模型模拟肯尼亚茜草科河骨木属植物的潜在分布及其在植物志中的应用初探

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植物科学学报 2020年第5期38卷 636-643页

作者：周亚东 mwangi Brian Njoroge Ndungu john Mbari 王生位胡光万王青锋中国科学院武汉植物园武汉430074 中国科学院中-非联合研究中心武汉430074 中国科学院大学北京100049

物种分布模型目前被广泛应用于生物学、生态学和保护生物学的各个领域。该文以肯尼亚茜草科河骨木属(Afrocanthium)为例,利用最大熵模型(MaxEnt)模拟植物在当前气候情景下的潜在分布,并将这些分布图利用于正在编写的《肯尼亚植物志》中... 详细信息

物种分布模型目前被广泛应用于生物学、生态学和保护生物学的各个领域。该文以肯尼亚茜草科河骨木属(Afrocanthium)为例,利用最大熵模型(MaxEnt)模拟植物在当前气候情景下的潜在分布,并将这些分布图利用于正在编写的《肯尼亚植物志》中。结果显示,基于足够的原始标本记录,模型能够很好地模拟出每种植物的潜在分布区域。相比传统和新一代植物志仅提供标本信息点或是粗略分布图,《肯尼亚植物志》预采用的潜在分布图,将为志书使用者提供更加全面、实用的信息。

关键词：物种分布模型气候因子 MaxEnt模型肯尼亚植物志

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Comparing Tree Heights among Montane Forest Blocks of Kenya Using LiDAR Data from GLAS

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Open Journal of Forestry 2015年第1期5卷 80-89页

作者： mwangi James Kinyanjui Ngugi john Kigomo Kamau Miriam Wambui Nderitu Joel Kariuki Nyanjui Charles Nganga john Macharia Ojijo William Odidi Ashiono Fredrick Owate Augustine Omamo Ndirangu Monicah Katumbi Department of Forestry School of Natural Resources and Environmental Studies Karatina University Karatina Kenya Department of Resource Surveys and Remote Sensing Nairobi Kenya Kenya Forest Research Institute Nairobi Kenya Kenya Forest Service Nairobi Kenya

This study was designed to use LiDAR data to research tree heights in montane forest blocks of Kenya. It uses a completely randomised block design to asses if differences exist in forest heights: 1) among montane forest blocks, 2) among Agro ecological zones (AEZ) within each forest block and 3) between similar AEZ in different forest blocks. Forest height data from the Geoscience Laser Altimeter System (GLAS) on the Ice Cloud and Land Elevation Satellite (ICE-SAT) for the period 2003-2009 was used for 2146 circular plots, of 0.2 - 0.25 ha in size. Results indicate that, tree height is largely influenced by Agro ecological conditions and the wetter zones have taller trees in the upper, middle and lower highlands. In the upper highland zones of limited human activity, tree heights did not vary among forest blocks. Variations in height among forest blocks and within forest blocks were exaggerated in regions of active human intervention.

关键词： Montane Forests Tree Height Agro Ecological Zones

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Removing subordinate species in a biodiversity experiment to mimic observational field studies

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Grassland Research 2022年第1期1卷 53-62页

作者： Bernhard Schmid Martin Schmitz Michael Rzanny Michael Scherer-Lorenzen Peter N.mwangi Wolfgang W.Weisser Andrew Hector Roland Schmid Dan F.B.Flynn Remote Sensing Laboratories Department of GeographyUniversity of ZurichZurichSwitzerland Department of Planning and Energy Municipality of ThalwilThalwilSwitzerland Department Biogeochemical Integration Max Planck Institute for BiogeochemistryJenaGermany Geobotany Faculty of BiologyUniversity of FreiburgFreiburgGermany Department of Botany Jomo Kenyatta University of Agriculture and TechnologyNairobiKenya Department of Life Science Systems School of Life SciencesTechnical University of MunichFreisingGermany Department of Plant Sciences University of OxfordOxfordUK Mirai Solutions GmbH ZurichSwitzerland Energy Analysis&Sustainability John A.Volpe National Transportation Systems CenterCambridgeMassachusettsUSA

Background:Positive effects of plant species richness on community biomass in biodiversity experiments are often stronger than those from observational field *** may be because experiments are initiated with randomly assembled species compositions whereas field communities have experienced ***:We compared aboveground biomass production of randomly assembled communities of 2–16 species(controls)with experimentally filtered communities from which subordinate species were removed,resulting in removal communities of 1–8 ***:Removal communities had(1)12.6%higher biomass than control communities from which they were derived,that is,with double species richness and(2)32.0%higher biomass than control communities of equal *** differences were maintained along the richness *** increased productivity of removal communities was paralleled by increased species evenness and ***:Result(1)indicates that subordinate species can reduce community biomass production,suggesting a possible explanation for why the most diverse field communities sometimes do not have the highest ***(2)suggests that if a community of S species has been derived by filtering from a pool of 2S randomly chosen species it is more productive than a community derived from a pool of S randomly chosen species without filtering.

关键词： environmental filtering Jena Experiment plant community species pool species richness

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Vulnerability of Kenya’s Water Towers to Future Climate Change: An Assessment to Inform Decision Making in Watershed Management

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American Journal of Climate Change 2020年第3期9卷 317-353页

作者： Kenneth Kemucie mwangi Anthony M. Musili Viola A. Otieno Hussen S. Endris Geoffrey Sabiiti Mohammed A. Hassan Abebe Tadege Tsehayu Artan Guleid Zachary Atheru Alphonce C. Guzha Thomas De Meo Nikola Smith Dickson Lubanga Makanji john Kerkering Brehan Doud Enock Kanyanya IGAD Climate Prediction and Applications Centre Nairobi Kenya USDA Forest Service International Programs c/o African Wildlife Foundation (AWF) Karen Kenya USDA Forest Service Pacific Northwest Region Portland OR USA Egerton University Njoro Kenya USDA Forest Service International Programs Washington DC USA USDA Forest Service International Programs Seattle USA USAID Kenya and East Africa Nairobi Kenya

Recent trends show that in the coming decades, Kenya’s natural resources will continue to face significant pressure due to both anthropogenic and natural stressors, and this will have greater negative impacts on socio-economic development including food security and livelihoods. Understanding the impacts of these stressors is an important step to developing coping and adaptation strategies at every level. The Water Towers of Kenya play a critical role in supplying ecosystems services such as water supply, timber and non-timber forest products and regulating services such as climate and water quantity and quality. To assess the vulnerability of the Water Towers to climate change, the study adopted the IPCC AR4 framework that defines vulnerability as a function of exposure, sensitivity, and adaptive capacity. The historical trends in rainfall indicate that the three Water Towers show a declining rainfall trend during the March-April-May (MAM) main rainy season, while the October-November-December (OND) short rainy season shows an increase. The temperature patterns are consistent with the domain having a common rising trend with a rate in the range of 0.3°C to 0.5°C per decade. Projection analysis considered three emissions scenarios: low-emission (mitigation) scenario (RCP2.6), a medium-level emission scenario (RCP4.5), and a high-emission (business as usual) scenario (RCP8.5). The results of the high-emission scenario show that the annual temperature over the Water Towers could rise by 3.0°C to 3.5

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