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Viability of combining microalgae and macroalgae cultures for treating anaerobically digested piggery effluent

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Journal of Environmental Sciences 2019年第8期31卷 132-144页

作者： Ashiwin Vadiveloo emeka Godfrey Nwoba Navid Reza Moheimani Algae R&D Centre School of Veterinary and Life Sciences Murdoch University Centre for Sustainable Aquatic Ecosystems Harry Butler Institute Murdoch University

Algal phytoremediation represents a practical green solution for treating anaerobically digested piggery effluent(ADPE). The potential and viability of combining microalgae and macroalgae cultivation for the efficient treatment of ADPE were evaluated in this *** the ability of different locally isolated macroalgae species illustrated the potential of Cladophora sp. to successfully grow and treat ADPE with up to 150 mg/L NH_4^+ with a biomass productivity of(0.13 ± 0.02) g/(L·day) and ammonium removal rate of(10.23 ± 0.18) mg/(L·day) NH_4^+. When grown by itself, the microalgae consortium used in this study consisting of Chlorella sp. and Scenedesmus sp. was found to grow and treat undiluted ADPE(up to 525 mg/L NH_4^+) with an average ammonium removal rate of 25 mg/(L·day) NH_4^+ and biomass productivity of(0.012 ± 0.0001) g/(L·day). Nevertheless, when combined together, despite the different cultivation systems(attached and non-attached) evaluated,microalgae and macroalgae were unable to co-exist together and treat ADPE as their respective growth were inversely related to each other due to direct competition for nutrients and available resources as well as the negative physical interaction between both algal groups.

关键词： Phytoremediation Piggery effluent Co-cultivation Cladophora Chlorella sp. Scenedesmus sp

Synergetic effect of graphene and Co(OH)2 as cocatalysts of TiO2 nanotubes for enhanced photogenerated cathodic protection

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Journal of Materials Science & Technology 2020年第2期37卷 55-63页

作者： Xiayu Lu Li Liu Xuan Xie Yu Cui emeka E.Oguzie Fuhui Wang Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang110016China School of Materials Science and Engineering University of Science and Technology of ChinaShenyang110016China Key Laboratory for Anisotropy and Texture of Materials(Ministry of Education) School of Materials Science and EngineeringNortheastern UniversityShenyang110819China Electrochemistry and Materials Science Research Laboratory Department of ChemistryFederal University of TechnologyP.M.B.1526OwerriNigeria

A layer of graphene(GR)particles was successfully deposited at the interface between Co(OH)2 nanoparticles and TiO2 nanotubes,aiming to improve the photoelectrochemical performance of the large-bandgap semiconductor *** obtained Co(OH)2/GR/TiO2 was extensively characterized by X-ray diffraction(XRD),scanning electron microscopy(SEM),transmission electron microscopy(TEM),X-ray photoelectron spectroscopy(XPS),UV–vis absorption spectra and photoluminescence(PL)emission *** impedance spectra,photogenerated potential-time(E-t),photocurrent density-time(i-t)and i-E curves and open circuit potential(OCP)curves were measured to investigate the photoelectrochemical activities and photogenerated cathodic protection *** results revealed that Co(OH)2/GR/TiO2 exhibits excellent photoelectrochemical and photogenerated cathodic performance due to synergistic effect between Co(OH)2 and ***(OH)2 and graphene co-modified TiO2 photoanode could provide an effective protection for 304 stainless steel(304 SS)in 3.5 wt%Na Cl solution for 12 h,which would be promising for future practical applications in the field of marine corrosion protection.

关键词： TiO2 nanotubes Graphene Co(OH)2 nanoparticles Photoelectrochemical performance Photogenerated cathodic protection

LIMITATIONS OF CANCER MARGIN DELINEATION BY MEANS OF AUTOFLUORESCENCE IMAGING UNDER CONDITIONS OF LASER SURGERY

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Journal of Innovative Optical Health Sciences 2010年第1期3卷 45-51页

作者： ALEXANDRE DOUPLIK AZHAR ZAM RALPH HOHENSTEIN ANGELOS KALITZEOS emeka NKENKE FLORIAN STELZLE SAOT—Erlangen Graduate School in Advanced Optical Technologies Friedrich-Alexander University Erlangen NurembergGermany Department of Photonic Technologies Friedrich-Alexander University Erlangen NurembergGermany Department of Oral and Maxillofacial Surgery Friedrich-Alexander University Erlangen NurembergGermany

Limitations of cancer margin delineation and surgical guidance by means of autofluorescence imaging under conditions of laser ablation were investigated and preliminary results are ***^(TM)(Novadaq Technologies Inc.,Canada)was used to capture digital images and Er:YAG laser(2.94μm,Glissando,WaveLight^(TM),Germany)was exploited to cause laser ablation on both normal and cancer sites of the *** was shown that changes of the autofluorescence image after ablation extend beyond the actual sizes of the ablation *** tumor tissue after the laser ablation starts to emit fluorescent light within the green wavelength band(490-550nm)similar to normal tissue stating that the current technology of in-process tissue classification ***,when the autofluorescence was collected in the red range(600-750nm),then the abnormal/normal contrast was reduced,but still present even after the laser *** present study highlights the importance of finding a proper technology for surgical navigation of cancer removal under conditions of high power effects in biological tissues.

关键词： Cancer margin delineation surgical guidance surgical navigation autofluorescence imaging laser surgery laser ablation

Cross-comparative review of Machine learning for plant disease detection:apple,cassava,cotton and potato plants

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Artificial Intelligence in Agriculture 2024年第2期12卷 127-151页

作者： James Daniel Omaye emeka Ogbuju Grace Ataguba Oluwayemisi Jaiyeoba Joseph Aneke Francisca Oladipo Department of Computer Science Federal UniversityLokojaNigeria Department of Computer Science Dalhousie UniversityHalifaxCanada Department of Computer Science Hampton UniversityVirginiaUSA

Plant disease detection has played a significant role in combating plant diseases that pose a threat to global agri-culture and food *** these diseases early can help mitigate their impact and ensure healthy crop *** learning algorithms have emerged as powerful tools for accurately identifying and classifying a wide range of plant diseases from trained image datasets of affected *** algorithms,including deep learning algorithms,have shown remarkable success in recognizing disease patterns and early signs of plant *** early detection,there are other potential benefits of machine learning algorithms in overall plant disease management,such as soil and climatic condition predictions for plants,pest identification,proximity detection,and many *** the years,research has focused on using machine-learning algorithms for plant disease ***,little is known about the extent to which the research community has ex-plored machine learning algorithms to cover other significant areas of plant disease *** view of this,we present a cross-comparative review of machine learning algorithms and applications designed for plant dis-ease detection with a specific focus on four(4)economically important plants:apple,cassava,cotton,and *** conducted a systematic review of articles published between 2013 and 2023 to explore trends in the research community over the *** filtering a number of articles based on our inclusion criteria,including articles that present individual prediction accuracy for classes of disease associated with the selected plants,113 articles were considered *** these articles,we analyzed the state-of-the-art techniques,challenges,and future prospects of using machine learning for disease identification of the selected *** from our re-view show that deep learning and other algorithms performed significantly well in detecting plant *** addition,we fou

关键词： Machine learning Plant diseases Agriculture Plant disease management Convolutional neural networks

Multifunctional superhydrophobic coatings fabricated from basalt scales on a fluorocarbon coating base

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Journal of Materials Science & Technology 2021年第25期84卷 86-96页

作者： Hongpeng Zheng Li Liu Fandi Meng Yu Cui Zhong Li emeka E.Oguzie Fuhui Wang Shenyang National Laboratory for Materials Science Northeastern UniversityNo.3-11 Wenhua RoadShenyang110819PR China Institute of Metal Research Chinese Academy of SciencesWencui Rd 62Shenyang110016PR China Africa Centre of Excellence in Future Energies and Electrochemical Systems Federal University of Technology OwerriPMB 1526OwerriImo StateNigeria

Superhydrophobic coatings are increasingly being evaluated as anticorrosion interventions in exceedingly hydrated ***,concerns about their long-term durability and amenability to large-area applications in marine environments are still hindering commercial-scale *** study is focused on development of easy-to-apply superhydrophobic coatings,with multifunctional capabilities,in order to extend the integrity and durability of the coatings in harsh marine ***,a set of facile methods involving selective chemical etching using concentrated Na OH,as well as fluorination with perfluoropolyether methyl ester were adopted to fabricate a superhydrophobic surface on basalt scales,having the required rough hierarchical micro-nanotextured and low surface *** superhydrophobic basalt scales were subsequently aligned atop a fluorocarbon resin,pre-deposited on a metal substrate,to yield a multifunctional superhydrophobic coating(3μL water droplet;contact angle=165.1°,rolling angle=0.7°),easily amenable to large surface area application and having excellent wear resistance,UV-aging resistance,salt spray resistance,corrosion resistance and antibacterial capabilities.

关键词： Basalt scales Multifunctional Superhydrophobic Chemical etching Fluoridation

Exploring the Social Impact of the Short-Stay Market(SSM)in Regional Areas:An Empirical Study

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Fudan Journal of the Humanities and Social Sciences 2024年第2期17卷 243-277页

作者： emeka Ndaguba Kerry Brown Dora Marinova Uma Jogulu School of Business and Law Edith Cowan UniversityPerthAustralia Curtin University Sustainability Policy Institute Curtin UniversityPerthAustralia

The discourse on microentrepreneurs and their involvement in the short stay market (SSM) was non-existent until 2008. While several concepts and constructs have been developed and empirically tested since 2009, many of them relate to economics, leaving the social, cultural, and environmental factors underdeveloped. Thus, this study aimed to fll the gap and identify and assess the social impact of the short-stay market (SSM) in a regional area. The study included 16 face-to-face interview sessions conducted with 18 participants, and the Leximancer software was employed to analyse the data. The study revealed that the social impact on SSM is not generic, rather pluralistic, multidimensional, and dynamic. The study also found that the limitation clause instituted by the council is a direct disconnect between the council and property owners/managers. Furthermore, despite ample opportunities provided by the short-stay market (SSM) in regional areas, encumbrances cannot be overlooked. Therefore, there is a need for a comprehensive approach to understand the social impact on policy frameworks in regional areas.

关键词： Short-stay market Experience economy Long-term rentals Wine economy Regulation

Assessment of Rational Prescribing in General Outpatient Department of Kampala International University Teaching Hospital, Western Uganda

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Pharmacology & Pharmacy 2019年第1期10卷 48-60页

作者： Amamchukwu ambrose Akunne Wafula Innocent Lam Joseph O. C. Ezeonwumelu Jennifer Chibuogwu Ebosie Bede emeka Udechukwu Department of Clinical Pharmacy and Biopharmacy School of Pharmacy Kampala International University Western Campus Ishaka Uganda Department of Pharmacology and Toxicology Kampala International University Western Campus Ishaka Uganda

Introduction: Prevention of irrational use of medicines may reduce healthcare costs and potentially save lives. Aim: The aim of this study was to assess rational drug prescribing using World Health Organization (WHO) and International Network of Rational Use of Drugs (INRUD) indicators on prescribing in the General Outpatient Department of Kampala International University Teaching Hospital, Ishaka-Bushenyi, Western Uganda. Methodology: The study design was retrospective, descriptive and cross-sectional. A total of 884 prescriptions were selected by systematic sampling using an interval of 27 from 23,868 prescriptions available in the medical records of the General Out-Patient Department (GOPD) of Kampala International University Teaching Hospital (KIUTH) from April, 2016 to March, 2017. The selected samples were analyzed using Microsoft Excel 2013, to assess for conformity with the prescribing indicators. Results: The results showed that the percentage of recording of diagnosis was 90.72% (index of diagnosis—0.91). The average number of drugs per encounter was 2.6 (index of non-polypharmacy—0.77), and the percentage of drugs prescribed with the generic name was 90.21% (index of generics—0.9). Percentages of encounters with antibiotics and injectable drugs prescribed were 61.88% (index of antibiotics—0.48) and 5.43% (index of injectable drugs—1) respectively. Only 78.96% (index of EMSLU—0.79) of the medicines prescribed were from the Essential Medicines Supplies List of Uganda (EMSLU) or Uganda Clinical Guidelines 2016. The index of rational drug prescribing (IRDP) was found to be 4.85. Conclusion: The findings showed that only the percentage of encounters with injectable drugs was in line with WHO/INRUD prescribing indicators. On the over all, the index of rational drug prescribing (IRDP) was poor (observed 4.85 versus optimum 6). The authors recommended continuous sensitization, counselling and education of prescribers in KIUTH in order to achieve rational prescrib

关键词： KIUTH INRUD indicators Keywords: Rational drug prescribing Uganda WHO GOPD

Application of Machine Learning for Flood Prediction and Evaluation in Southern Nigeria

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Atmospheric and Climate Sciences 2024年第3期14卷 299-316页

作者： emeka Bright Ogbuene Chukwumeuche ambrose Eze Obianuju Getrude Aloh Andrew Monday Oroke Damian Onuora Udegbunam Josiah Chukwuemeka Ogbuka Fred emeka Achoru Vivian Amarachi Ozorme Obianuju Anwara Ikechukwu Chukwunonyelum Anthonia Nneka Nebo Obiageli Jacinta Okolo Centre for Environmental Management and Control (CEMAC) University of Nigeria Enugu Nigeria Department of Geography Enugu State University of Science and Technology ESUT Enugu Nigeria School of Civil Engineering Newcastle University Newcastle upon Tyne UK

This study explored the application of machine learning techniques for flood prediction and analysis in southern Nigeria. Machine learning is an artificial intelligence technique that uses computer-based instructions to analyze and transform data into useful information to enable systems to make predictions. Traditional methods of flood prediction and analysis often fall short of providing accurate and timely information for effective disaster management. More so, numerical forecasting of flood disasters in the 19th century is not very accurate due to its inability to simplify complex atmospheric dynamics into simple equations. Here, we used Machine learning (ML) techniques including Random Forest (RF), Logistic Regression (LR), Naïve Bayes (NB), Support Vector Machine (SVM), and Neural Networks (NN) to model the complex physical processes that cause floods. The dataset contains 59 cases with the goal feature “Event-Type”, including 39 cases of floods and 20 cases of flood/rainstorms. Based on comparison of assessment metrics from models created using historical records, the result shows that NB performed better than all other techniques, followed by RF. The developed model can be used to predict the frequency of flood incidents. The majority of flood scenarios demonstrate that the event poses a significant risk to people’s lives. Therefore, each of the emergency response elements requires adequate knowledge of the flood incidences, continuous early warning service and accurate prediction model. This study can expand knowledge and research on flood predictive modeling in vulnerable areas to inform effective and sustainable contingency planning, policy, and management actions on flood disaster incidents, especially in other technologically underdeveloped settings.

关键词： Machine Learning Flood Prediction Evaluation Southern Nigeria

Comparative analysis of urinary schistosomiasis among primary school children and rural farmers in Obollo-Eke,Enugu State,Nigeria:Implications for control

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Asian Pacific Journal of Tropical Medicine 2012年第10期5卷 796-802页

作者： Celestine Chidi Ogbonna Geme Urge Dori emeka Innocent Nweze Gilbert Muoneke Innocent Ejike Nwankwo Nkiru Akputa Department of Microbiology University of NigeriaNsukkaNigeria Microbiology Laboratory School of Bioscience and BiotechnologyUniversity of CamerinoVia Gentile Ⅲ da Varano62032 Camerino(MC)Italy Department of Experimental Medicine and Public Health Polo delle Scienze "Domenico Amici"Via Madonna delle CarceriUniversity of Camerino62032(MC)Italy Faculty of Medicine Addis Ababa UniversityEthiopia Department of Dermatology University Hospitals of ClevelandOhioUnited States Department of Medical Parasitology University of Nigeria Teaching Hospital EnuguNigeria Consolata Medical Diagnostic Laboratory St Theresa's Hospital5B New Markurdi RoadObollo AforEnugu StateNigeria

Objective:To determine the prevalence,sex-age related intensity of urinary schistosomiasis and to compare such parameters among rural school children and rural fanners in selected communities in Obollo-Eke located in Southeast,***:A cross-sectional survey involving 1 337 school children and farmers was conducted in Obollo-Eke community between September 2006 and July *** data of subjects was collected using a questionnaire prepared for this *** samples were collected and examined for haematuria and ova of Schistosoma haematobium(***) using Medi-test Combi 9 and sedimentation technique ***:The prevalence of urinary schistosomiasis based on microscopic examination of the urine sediment for the ova of *** was 17.5%while the prevalence of haematuria was 15.6%.Infection intensity varied from light to *** general,the prevalence was higher among males(20.8%) than females(14.6%;P>0.05) and was slightly higher among primary school children(18.0%;n=762) than farmers(16.9%;n=575;P>0.05).The age-specific prevalence of schistosomiasis among the study subjects ranged from 8.3%to 21.2%in 0-5 years and 11-15 years age groups ***:Haematuria and mean egg/10 mL urine (r = 0.95;P<0.01) showed that both procedures are reliable for the diagnosis of the disease and can be used to ascertain the prevalence of the disease in any *** comparative analysis of urinary bilharziasis among primary school children and rural farmers demonstrated that the infection is moderately high in these two risk population groups at Obollo-Eke.A robust intervention strategy is clearly needed.

关键词： Urinary schistosomiasis School children Rural farmers Prevalence Nigeria