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14篇 您的检索式:作者名="Eyo"
    题名 作者 年代 出处 被引量
1Day surgery: Are we transferring the burden of care?显示文摘I Udo C Eyo 2014Nigerian Journal of Clinical Practice2014,,4:1
2P2X7 receptor activation regulates microglial cell death during oxygen-glucose deprivation显示文摘Eyo UB Miner SA Ahlers KE et ai 2013Neuropharmacology2013,73,11:1
3Bidirectional microglia-neuron communication in the healthy brain显示文摘Eyo UB Wu lJ 2013Neural Plast2013,2013,45:1
4Neuronal hyperactivity recruits microglial processes via neuronal NMDA receptors and microglial P2Y12 receptors after status epilepticus显示文摘Eyo UB Peng J Swiatkowski P 2014J Neurosci2014,34,10:1
5Conservation of antigenicity in a 31 -kDa Brucella protein 显示文摘BRICKER B J TABATABAI L B I)EYOE B L 1998Vet Microbiol1998,18,34:1
6GIS cellular automata using Artificial neural network for land use change simulation of Lagos, Nigeria显示文摘Onuwa Okwuashi Mfon Isong Etim Eyo 2012Journal of Geography and Geology2012,4,2:1
7P2X7 receptor activation regulates micmglial cell death during oxygen-glucose deprivation 显示文摘Eyo UB Miner SA Ahlers KE 2013Neuropharmacology2013,73,10:1
8Bidirectional microglia-neuron co mmol/Lunication in the healthy brain显示文摘Eyo UB Wu LJ 2013Neural Plast2013,2013,241:1
9Microglia P2Y12 receptors regulate microglia activation andsurveillance during neuropathic pain显示文摘Gu N Eyo UB Murugan M 2015Brain Behav Immuny2015,,30:1
10Bidirectional microglia-neuron communication in the healthy brain显示文摘Eyo UB Wu LJ 2013Neural Plast2013,2013,45:1
11Comparative Study of the Growth and Gonad Development of Clarias gariepinus (Burchell 1822) Fed Diets with Plant and Animal-based Ingredients in Concrete Tanks显示文摘Albert Philip Ekanem Sunday Urom Eteng Francis Maduwuba Nwosu Victor Oscar Eyo 2012Journal of Agricultural Science and Technology(A)2012,2,10:1
12The Playwright, Creativity, and Society: Unpacking Sunnie Ododo's To Return From the Void显示文摘King Akan Nnaemeka Eyo 2015Journal of Sociology Study2015,5,2:0
13Multiclass stand-alone and ensemble machine learning algorithms utilised to classify soils based on their physico-chemical characteristics显示文摘This study has provided an approach to classify soil using machine learning.Multiclass elements of stand-alone machine learning algorithms(i.e.logistic regression(LR)and artificial neural network(ANN)),decision tree ensembles(i.e.decision forest(DF)and decision jungle(DJ)),and meta-ensemble models(i.e.stacking ensemble(SE)and voting ensemble(VE))were used to classify soils based on their intrinsic physico-chemical properties.Also,the multiclass prediction was carried out across multiple cross-validation(CV)methods,i.e.train validation split(TVS),k-fold cross-validation(KFCV),and Monte Carlo cross-validation(MCCV).Results indicated that the soils’clay fraction(CF)had the most influence on the multiclass prediction of natural soils’plasticity while specific surface and carbonate content(CC)possessed the least within the nature of the dataset used in this study.Stand-alone machine learning models(LR and ANN)produced relatively less accurate predictive performance(accuracy of 0.45,average precision of 0.5,and average recall of 0.44)compared to tree-based models(accuracy of 0.68,average precision of 0.71,and recall rate of 0.68),while the meta-ensembles(SE and VE)outperformed(accuracy of 0.75,average precision of 0.74,and average recall rate of 0.72)all the models utilised for multiclass classification.Sensitivity analysis of the meta-ensembles proved their capacities to discriminate between soil classes across the methods of CV considered.Machine learning training and validation using MCCV and KFCV methods enabled better prediction while also ensuring that the dataset was not overfitted by the machine learning models.Further confirmation of this phenomenon was depicted by the continuous rise of the cumulative lift curve(LC)of the best performing models when using the MCCV technique.Overall,this study demonstrated that soil’s physico-chemical properties do have a direct influence on plastic behaviour and,therefore,can be relied upon to classify soils.Eyo Eyo Samuel Abbey 2022Journal of Rock Mechanics and Geotechnical Engineering2022,14,2:0
14小胶质细胞在多种实验性癫痫发作模型中发挥有益作用显示文摘癫痫发病率高,影响各年龄层次,包括年轻人和老年人。目前临床上使用的抗癫痫药物都是根据已知的以神经元为中心的机制研发,但有约1/3的患者对现有药物的治疗无效。因此,有必要对癫痫产生和持续的其他替代和补充机制进行研究。神经炎症,广义上定义为中枢神经系统中免疫细胞和分子的激活。研究发现,神经炎症促进癫痫的发生,但参与该病理生理过程的特定细胞尚不清楚。小胶质细胞是大脑的主要炎症细胞。因为既往研究使用的方法对小胶质细胞的特异性较低,或者存在固有的混淆,所以小胶质细胞的作用一直存在争议。使用一种选择性靶向小胶质细胞的方法(以避免上述副作用),我们发现了小胶质细胞在限制化学惊厥、电性和高热性癫痫发作方面有广泛有益作用,并进一步发现小胶质细胞对控制癫痫发作的作用。Synphane Gibbs-Shelton Jordan Benderoth Ronald P Gaykema Justyna Straub Kenneth A Okojie Joseph O Uweru Dennis H Lentferink Binita Rajbanshi Maureen N Cowan Brij Patel Anthony Brayan Campos-Salazar Edward Perez-Reyes Ukpong B Eyo 杜一星(编译) 2023神经损伤与功能重建2023,18,6:0
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