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山东大学脑科学团队联合挪威卑尔根大学在Neuro-Oncology发表Letter文章
山东大学齐鲁医院 山东大学脑与类脑科学研究院 卑尔根大学 Neuro-Oncology 胶质瘤
2020/5/17
日前，山东大学齐鲁医院、脑与类脑科学研究院李新钢、王剑课题组联合挪威卑尔根大学Rolf Bjerkvig教授带领的脑科学团队在神经肿瘤学期刊Neuro-Oncology（一区，影响因子10.091）上发表题为“A Validated Prognostic Nomogram for Patients With Newly Diagnosed Lower-Grade Gliomas in a Larg...
miR-139在Aβ25-35诱导Neuro-2a细胞损伤中的机制研究
miR-139 FOXO1 NF-κB 阿尔茨海默病
2020/10/27
研究miR-139在Aβ25-35诱导的Neuro-2a细胞损伤中的作用,探讨其在AD发生发展中的作用及分子机制。方法 首先应用Aβ25-35体外构建Neuro-2a细胞损伤模型,采用qRT-PCR和Western blot技术检测不同浓度Aβ25-35对Neuro-2a细胞miR-139和FOXO1 mRNA及蛋白表达的影响。应用荧光素酶报告法测定miR-139的潜在作用靶点,并验证FOXO1作...
2018年SPIE神经激发光子计算研讨会（SPIE Neuro-inspired Photonic Computing Workshop）
2018年 SPIE 神经激发光子计算 研讨会
2017/10/27
Our increasing needs in information processing cannot be met with current electronic technologies. This statement is receiving a significant audience today considering the physical limitation in trans...
近日，国际权威神经肿瘤学期刊，美国、日本以及欧洲神经肿瘤协会官方杂志Neuro-Oncology（2016年影响因子7.786）在线发表了我校神经系统疾病研究所的研究论文《Golgi phosphoprotein 3 promotes glioma progression via inhibiting Rab5-mediated endocytosis and degradation of epi...
Neuro-fuzzy modeling for crop yield prediction
Neural Networks Neuro-Fuzzy Fuzzy Neural Networks
2015/8/20
The purpose of this paper is to explore the dynamics of neural networks in forecasting crop (wheat) yield using remote sensing and
other data. We use the Adaptive Neuro-Fuzzy Inference System (ANFIS)...
Estimation of Aquifer Transmissivity using Kriging, Artificial Neural Network, and Neuro-Fuzzy models
ransmissivity Kriging Artificial Neural Network ANFIS Neuro-Fuzzy interpolation groundwater
2015/8/11
In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult t...
Prediction of Ground Water Vulnerability using an Integrated GIS-based neuro-fuzzy techniques
Geographic Information System GIS
2015/8/6
There is a need to develop new modeling techniques that assess ground water vulnerability with less expensive data and which are robust when data are uncertain and incomplete. Incorporation of Geograp...
Cognitive functions such as a perception, thinking and acting are based on the working of the brain, one of the most complex systems we know. The traditional scientific methodology, however, has prove...
A COMPARISON OF NEURO-FUZZY AND TRADITIONAL IMAGE SEGMENTATION METHODS FOR AUTOMATED DETECTION OF BUILDINGS IN AERIAL PHOTOS
neural segmentation classifi cation
2015/3/24
Using a set of colour-infrared aerial photos, we compare a newly developed neural net based clustering method with a
method based on the classical ISODATA algorithm. The primary focus is on the detec...
Application of Neuro-Genetic Algorithm to Determine Reservoir Response in Different Hydrologic Adversaries
neuro-genetic models reservoir response
2015/3/1
The hydrologic adversaries like high magnitude storms, extreme dryness, aridity, more than normal
demand for water etc. often cause a huge stress on the storage structures such as reservoirs and che...
Estimation of Aquifer Transmissivity using Kriging, Artificial Neural Network, and Neuro-Fuzzy models
Neuro-Fuzzy interpolation groundwater
2015/1/6
In interpolation of groundwater properties such as transmissivity, due to the unknown distributed values of the variables and heterogenity, the best and the unbiased aspects are frequently difficult t...
Prediction of Ground Water Vulnerability using an Integrated GIS-based neuro-fuzzy techniques
Geographic Information System GIS Spatial Modeling Remote Sensing Fuzzy Logic Neural Networks
2015/1/4
There is a need to develop new modeling techniques that assess ground water vulnerability with less expensive data and which are robust when data are uncertain and incomplete. Incorporation of Geograp...
Risk Mapping of Cutaneous Leishmaniasis via a Fuzzy C Means-based Neuro-Fuzzy Inference System
Cutaneous Leishmaniasis Data Mining Fuzz C Means Clustering Neuro-Fuzzy Systems
2014/12/1
Finding pathogenic factors and how they are spread in the environment has become a global demand, recently. Cutaneous Leishmaniasis (CL) created by Leishmania is a special parasitic disease which can ...
Fuzzy-Neuro Model for Intelligent Credit Risk Management
Fuzzy Logic Neural Networks Fuzzy-Neuro Model Credit Risk Management
2013/1/28
This paper presents hybrid fuzzy logic and neural network algorithm to solve credit risk management problem. Credit risk is the risk of loss due to a debtor’s non-payment of a loan or other line of cr...
Inverse neuro-fuzzy MR damper model and its application in vibration control of vehicle suspension system
MRdamper ANFIS inverse model semi-active control LQG control vehicle suspension
2015/3/30
In this paper, a magneto-rheological (MR) damper-based semi-active controller for vehicle suspension is developed. This system consists of a linear quadratic Gauss (LQG) controller as the system contr...