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Collaborative Efforts and Strategies for Cholera Outbreak Control in Garissa County, Kenya: Implementation of Water Quality Monitoring Interventions

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Journal of Water Resource and Protection 2024年第2期16卷 123-139页

作者： Michael Habtu Mark Nanyingi Ali A. Hassan Abdiwahid M. Noor Joel Mutyandia Muli Alan Mwika Julius Wekesa ahmed Fidhow Diba Dulacha Landry Kabego Ishata Nannie Conteh Andre Arsene Bita Fouda Sonia Chene Aden H. Ibrahim ahmed nadhir omar Martins C. Livinus Abdourahmane Diallo World Health Organization Nairobi Kenya Department of Health Garissa County Government Garissa Kenya Water Resources Authority Garissa Kenya World Health Organization Regional Office for Africa Brazzaville Congo Regional Agency for Health Dijon France

A multi-faceted Case Area Targeted Intervention (CATI) approach emphasizing the integration of Water, Sanitation and Hygiene (WASH) interventions and Oral Cholera Vaccine (OCV) campaign was employed to respond to the outbreak of cholera in Garissa County. Drinking water sources in areas heavily impacted by cholera were systematically mapped and tested for microbiological quality. The quality assessment was carried out in April 2023 during an ongoing cholera outbreak in the county. A total of 109 samples were collected and tested for thermotolerant coliforms and other in situ parameters. The finding revealed that more than 87% of the samples did not meet the World Health Organization (WHO) standard for thermotolerant coliforms;and 30% had turbidity values above the recommended threshold values. None of the 109 samples had any traceable residual chlorine. Following these findings, the county government implemented the targeted interventions which resulted in a positive impact in the fight against cholera. The WHO supported key interventions which included capacity building in water quality monitoring and prepositioning of critical WASH commodities to the cholera affected areas.

关键词： Cholera Drinking Water Household Water Treatment Kenya

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Data-Driven Models for Predicting Solar Radiation in Semi-Arid Regions

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Computers, Materials & Continua 2023年第1期74卷 1625-1640页

作者： Mehdi Jamei Nadjem Bailek Kada Bouchouicha Muhammed A.Hassan ahmed Elbeltagi Alban Kuriqi nadhir Al-Ansar Javier Almorox El-Sayed M.El-kenawy Engineering Faculty Shohadaye Hoveizeh Campus of TechnologyShahid Chamran University of AhvazDashte AzadeganIran Energies and Materials Research Laboratory Department of Matter SciencesFaculty of Sciences and TechnologyUniversity of TamanghassetTamanghassetAlgeria Unitéde Recherche en Energies Renouvelables en Milieu Saharien(URERMS) Centre de Développement des Energies Renouvelables(CDER)01000AdrarAlgeria Mechanical Power Engineering Department Faculty of EngineeringCairo UniversityGiza12613GizaEgypt Agricultural Engineering Department Faculty of AgricultureMansoura UniversityMansoura35516Egypt CERIS Instituto Superior TécnicoUniversidade de LisboaLisbonPortugal Department of Civil Environmental and Natural Resources EngineeringLulea University of Technology97187LuleaSweden Universidad Politécnica de Madrid UPMAvd.Puerta de Hierro28040MadridSpain Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Solar energy represents one of themost important renewable energy sources contributing to the energy transition *** that the observation of daily global solar radiation(GSR)is not affordable in some parts of the globe,there is an imperative need to develop alternative ways to predict ***,the main objective of this study is to evaluate the performance of different hybrid data-driven techniques in predicting daily GSR in semi-arid regions,such as the majority of Spanish ***,four ensemble-based hybrid models were developed by hybridizing Additive Regression(AR)with Random Forest(RF),Locally Weighted Linear Regression(LWLR),Random Subspace(RS),and *** base algorithms of the developed models are scarcely applied in previous studies to predict solar *** testing phase outcomes demonstrated that the ARRF models outperform all other hybrid *** provided models were validated by statisticalmetrics,such as the correlation coefficient(R)and root mean square error(RMSE).The results proved that Scenario#6,utilizing extraterrestrial solar radiation,relative humidity,wind speed,and mean,maximum,and minimum ambient air temperatures as the model inputs,leads to the most accurate predictions among all scenarios(R=0.968–0.988 and RMSE=1.274–1.403 MJ/m^(2)・d).Also,Scenario#3 stood in the next rank of accuracy for predicting the solar radiation in both validating *** AD-RF model was the best predictive,followed by AD-RS and ***,this study recommends new effective methods to predict GSR in semiarid regions.

关键词： Solar radiation prediction random forest locally-weighted linear regression additive regression

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A GIS-Based Drastic Model for Assessing Aquifer Vulnerability in Amman-Zerqa Groundwater Basin, Jordan

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Engineering（科研） 2013年第5期5卷 490-504页

作者： Abdulla MAl-Rawabdeh nadhir AAl-Ansari ahmed AAl-Taani Sven Knutsson Department of Geomatics Engineering University of CalgaryAlbertaCanada Department of Civil Environmental and Natural Resources and EngineeringLulea University of TechnologyLuleaSweden UNESCO Chair for Desert Studies and Desertification Control Yarmouk UniversityIrbidJordan

Amman-Zerqa Basin (AZB) is a major basin in Jordan. The concentration of economic, agricultural and social activities within the basin makes it of prime importance to Jordan. Intensive agricultural practices are widespread and located close to groundwater wells, which pose imminent threats to these resources. Groundwater contamination is of particular concern as groundwater resources are the principal source of water for irrigation, drinking and industrial activities. A DRASTIC model integrated with GIS tool has been used to evaluate the groundwater vulnerability of AZB. The Drastic index map showed that only 1.2% of the basin’s total area of 3792 km2 lies in the no vulnerable zone and about 69% is classified as having low pollution potential. The results also revealed that about 30% of the catchment area is moderately susceptible to pollution potential and slightly 1% is potentially under high pollution risk. These results suggest that almost one third of the AZB is at moderate risk of pollution potential. These areas are mainly in the north-east and central parts of the basin where the physical factors (gentle slope and high water table) would allow more contaminants to easily move into the shallow groundwater aquifer. Areas with high vulnerability to pollution are largely located in the center of Amman old city.

关键词： Amman-Zerqa Basin Jordan GIS DRASTIC

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Behavior of Repairing Composite I-Section Beams with Opening under Ultimate Torque

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Engineering（科研） 2018年第4期10卷 202-214页

作者： Ali Sabah ahmed Al Amli nadhir Al-Ansari Yaarub G. Abtan Civil Engineering Department Al Mustansiriyah Engineering College Al Mustansiriyah University Baghdad Iraq Lulea Technology University Lulea Sweden

An experimental study was conducted to investigate the behavior of composite concrete beams damaged and cracked under pure torsion, and then repaired by external strengthening. This was achieved using high strength Carbon Fiber Reinforced Polymer (CFRP) laminates bonded with epoxy four composite modify reactive powder concrete (MRPC) I-beams. Different types of section (Solid & with opening) were tested to obtain the effect of amount of CFRP laminate on beams ultimate torque behavior, angle of twist and failure modes. The results obtained showed that a significant effect of external high strength CFRP laminates on effectively restore of section solid, the range of 89.8% to 91.2% of ultimate torsional strength effectively restored as well as effectively restoring of section opening by 83.48% - 86.67% of ultimate torsional strength. The repaired beams give high efficiency in ultimate torsional strength, and indicate that the adopted technique gives a good torsional strength.

关键词： MRPC Repairing Carbon Fiber Reinforced Polymer (CFRP) Ultimate Torsional Strength Composite Solid Opening

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Assessing the Efficacy of Improved Learning in Hourly Global Irradiance Prediction

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Computers, Materials & Continua 2023年第11期77卷 2579-2594页

作者： Abdennasser Dahmani Yamina Ammi Nadjem Bailek Alban Kuriqi nadhir Al-Ansari Salah Hanini Ilhami Colak Laith Abualigah El-Sayed M.El-kenawy Department of Mechanical Engineering Faculty of Science and TechnologyGIDD Industrial Engineering and Sustainable Development LaboratoryUniversity of RelizaneBourmadiaRelizane48000Algeria Laboratory of Biomaterials and Transport Phenomena(LBMPT) University of MedeaUrban PoleMedea26000Algeria Energies and Materials Research Laboratory Faculty of Sciences and TechnologyUniversity of TamanghassetTamanrasset10034Algeria Sustainable Development and Computer Science Laboratory Faculty of Sciences and TechnologyAhmed Draia University of AdrarAdrarAlgeria CERIS Instituto Superior TécnicoUniversidade de LisboaLisbon1049-001Portugal Civil Engineering Department University for Business and TechnologyPristina10000Kosovo Department of Civil Environmental and Natural Resources EngineeringLulea University of TechnologyLulea97187Sweden Engineering and Architecture Faculty Nisantasi UniversityIstanbulTurkey Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia Department of Computing and Information Systems School of Engineering and TechnologySunway University MalaysiaPetaling Jaya27500Malaysia Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt

Increasing global energy consumption has become an urgent problem as natural energy sources such as oil,gas,and uranium are rapidly running *** into renewable energy sources such as solar energy is being pursued to counter *** energy is one of the most promising renewable energy sources,as it has the potential to meet the world’s energy needs *** study aims to develop and evaluate artificial intelligence(AI)models for predicting hourly global *** hyperparameters were optimized using the Broyden-FletcherGoldfarb-Shanno(BFGS)quasi-Newton training algorithm and STATISTICA *** from two stations in Algeria with different climatic zones were used to develop the *** error measurements were used to determine the accuracy of the prediction models,including the correlation coefficient,the mean absolute error,and the root mean square error(RMSE).The optimal support vector machine(SVM)model showed exceptional efficiency during the training phase,with a high correlation coefficient(R=0.99)and a low mean absolute error(MAE=26.5741 Wh/m^(2)),as well as an RMSE of 38.7045 Wh/m^(2) across all ***,this study highlights the importance of accurate prediction models in the renewable energy,which can contribute to better energy management and planning.

关键词： Renewable energy energy prediction global irradiation artificial intelligence BFGS quasi-Newton training algorithm

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Evaluating Water Scarcity Indices for Cultivation Region in Sadat Al-Hindya, Babylon, Iraq: A Case Study

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Engineering（科研） 2023年第10期15卷 647-662页

作者： Ali Hassan Hommadi nadhir Abbas Al-Ansari ahmed Al Obaidy Wissam K. Obied Rafat N. Abdul-Ghni Sawan Ali Abed National Center for Water Resources management Ministry of Water Resources Baghdad Iraq Department of Civil Environmental and Natural Resources Engineering Lulea University of Technology Lulea Sweden Seneca Polytechnic Toronto Canada College of Science University of Al-Qadisiyah Diwaniyah Iraq

The study evaluated the Water Scarcity Indices for Cultivation Region in Sadat Al-Hindya, Babylon, Iraq. It calculated the reference evapotranspiration, actual evapotranspiration, and amount of precipitation with effective rainfall to estimate the droughts indicators which are the Standard Precipitation Index (SPI), the Standard Precipitation and Evaporation Rain Index (SPEI) and Reconnaissance Drought Index RDI. The study indicated that the greatest decrease in river flow occurred from 2019-2021 to 2020-2021 due to increasing temperature in summer and decreasing precipitation in winter. This research evaluated a wet and drought indicating for planning and management of water resources to face changes in climate of future. The research showed the last years were years of drought according to the three indicators. SPI ranged from 0.5 to 1.5 in the rainy years, but it was -0.5 to -1 as moderately dry because in the middle of Iraq while in the south of Iraq was severely dry or extremely dry. SPEI of the study area ranged from -1.5 to -2.5 which means severely dry. The SPEI measures are negative values meaning the months and years were drier. RDi ranged from 0 to -1 was dry and moderately dry while some months and years are positive and will be wet through rainfall for ten years (2014-2023). From indices showed that the region was a drying study area due to the impact of climate change because of the reduction of precipitation and increase in temperature which caused a rise of evapotranspiration during the last few years.

关键词： Drought Indices Evapotranspiration Precipitation Climate Change

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