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A mathematical model of synaptotagmin 7 revealing functional importance of short-term synaptic plasticity 预览
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作者 Yao He Don Kulasiri Jingyi Liang 《中国神经再生研究:英文版》 SCIE CAS CSCD 2019年第4期621-631,共11页
Synaptotagmin 7(Syt7),a presynaptic calcium sensor,has a significant role in the facilitation in shortterm synaptic plasticity:Syt7 knock out mice show a significant reduction in the facilitation.The functional import... Synaptotagmin 7(Syt7),a presynaptic calcium sensor,has a significant role in the facilitation in shortterm synaptic plasticity:Syt7 knock out mice show a significant reduction in the facilitation.The functional importance of short-term synaptic plasticity such as facilitation is not well understood.In this study,we attempt to investigate the potential functional relationship between the short-term synaptic plasticity and postsynaptic response by developing a mathematical model that captures the responses of both wild-type and Syt7 knock-out mice.We then studied the model behaviours of wild-type and Syt7 knock-out mice in response to multiple input action potentials.These behaviors could establish functional importance of short-term plasticity in regulating the postsynaptic response and related synaptic properties.In agreement with previous modeling studies,we show that release sites are governed by non-uniform release probabilities of neurotransmitters.The structure of non-uniform release of neurotransmitters makes shortterm synaptic plasticity to act as a high-pass filter.We also propose that Syt7 may be a modulator for the long-term changes of postsynaptic response that helps to train the target frequency of the filter.We have developed a mathematical model of short-term plasticity which explains the experimental data. 展开更多
关键词 SYNAPSE SHORT-TERM plasticity SHORT-TERM FACILITATION and depression MATHEMATICAL model low-frequency STIMULATION high-frequency STIMULATION
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The detrimental effects of lipopolysaccharideinduced neuroinflammation on adult hippocampal neurogenesis depend on the duration of the pro-inflammatory response 预览
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作者 Martha Pérez-Domínguez Evangelina Aila-Munz +1 位作者 Eduardo Domínguez-Rivas Angélica Zepeda 《中国神经再生研究:英文版》 SCIE CAS CSCD 2019年第5期817-825,共9页
Adult hippocampal neurogenesis is a finely tuned process regulated by extrinsic factors.Neuroinflammation is a hallmark of several pathological conditions underlying dysregulation of neurogenesis.In animal models,lipo... Adult hippocampal neurogenesis is a finely tuned process regulated by extrinsic factors.Neuroinflammation is a hallmark of several pathological conditions underlying dysregulation of neurogenesis.In animal models,lipopolysaccharide(LPS)-induced neuroinflammation leads to a neurogenic decrease mainly associated to the early inflammatory response.However,it is not well understood how the neuroinflammatory response progresses over time and if neurogenesis continues to be diminished during the late neuroinflammatory response.Moreover,it is unknown if repeated intermittent administration of LPS along time induces a greater reduction in neurogenesis.We administered one single intraperitoneal injection of LPS or saline or four repeated injections(one per week)of LPS or saline to young-adult mice.A cohort of new cells was labeled with three 5-bromo-2-deoxyuridine injections(one per day)4 days after the last LPS injection.We evaluated systemic and neuroinflammation-associated parameters and compared the effects of the late neuroinflammatory response on neurogenesis induced by each protocol.Our results show that 1)a single LPS injection leads to a late pro-inflammatory response characterized by microglial activation,moderate astrocytic reaction and increased interleukin-6 levels.This response correlates in time with decreased neurogenesis and 2)a repeated intermittent injection of LPS does not elicit a late pro-inflammatory response although activated microglia persists.The latter profile is not accompanied by a continued longterm hippocampal neurogenic decrease.Hereby,we provide evidence that the neuroinflammatory response is a dynamic process that progresses in a milieu-dependent manner and does not necessarily lead to a neurogenic decrease,highlighting the complex interaction between the immune system and neurogenesis. 展开更多
关键词 DENTATE GYRUS subgranular zone inflammation microglia ASTROCYTES IL-6 cytokines cell proliferation neural progenitor cells IMMATURE neurons long-term short-term adult hippocampal NEUROGENESIS
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额颞蛛网膜囊肿认知功能障碍及其在神经内镜术后近期和远期的情况比较 预览
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作者 王金伟 欧益金 +3 位作者 穆林森 覃洁 胡凤兴 彭玉平 《广东医学》 CAS 2019年第11期1563-1567,共5页
目的探讨额颞蛛网膜囊肿(FTAC)认知功能障碍及其神经内镜术后近期和远期的改善情况。方法纳入29例FTAC手术(Ⅰ组)、16例FTAC非手术(Ⅱ组)、10例健康人(Ⅲ组)分别在术前2周(T1)、术后3个月(T2)、术后1年(T3)或相等的时间段间隔点进行认... 目的探讨额颞蛛网膜囊肿(FTAC)认知功能障碍及其神经内镜术后近期和远期的改善情况。方法纳入29例FTAC手术(Ⅰ组)、16例FTAC非手术(Ⅱ组)、10例健康人(Ⅲ组)分别在术前2周(T1)、术后3个月(T2)、术后1年(T3)或相等的时间段间隔点进行认知功能测验,采用重复测量方差分析比较评分;T1时3组量表评分行效度、信度检验,Ⅰ组和Ⅱ组额颞间、左右间评分均行t检验,颞叶囊肿不同Galassi分型间评分行方差分析。结果3组间评分差异有统计学意义(P<0.05),不同时间点间差异有统计学意义(P<0.05),存在交互作用(P<0.05):T1时Ⅰ组和Ⅱ组差异无统计学意义(P>0.05),但均差于Ⅲ组(P<0.05);T2或T3时Ⅰ组评分较T1改善(P<0.05)。T1时,效度检验因子载荷均>0.80,克朗巴赫系数0.70,额颞间评分差异无统计学意义(P>0.05),左侧抑制/转换测验评分差于右侧(P<0.05),不同Galassi分型间评分差异无统计学意义(P>0.05)。结论FTAC可引起基本和高级认知功能障碍;神经内镜术后认知功能改善,疗效长久稳定;认知功能障碍可作为术前考虑的手术适应证;左侧囊肿可能影响言语应变;囊肿大小与认知功能障碍缺少相关性。 展开更多
关键词 额颞蛛网膜囊肿 认知功能障碍 神经内镜 近期 远期
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他克莫司治疗难治性重症肌无力的短期疗效观察 预览
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作者 王玉环 韦贺 刘敏 《神经损伤与功能重建》 2019年第5期228-231,共4页
目的:观察不同剂量他克莫司治疗难治性重症肌无力患者的短期疗效。方法:纳入32例难治性重症肌无力患者,分为A(2 mg/d)、B(3 mg/d)两组进行治疗,分析第2、4、12周疗效,并记录不良反应。结果:25例患者完成试验,A组11例,B组14例。与治疗前... 目的:观察不同剂量他克莫司治疗难治性重症肌无力患者的短期疗效。方法:纳入32例难治性重症肌无力患者,分为A(2 mg/d)、B(3 mg/d)两组进行治疗,分析第2、4、12周疗效,并记录不良反应。结果:25例患者完成试验,A组11例,B组14例。与治疗前相比,A组在治疗4、12周时MG临床评分均显著降低(P<0.05);B组在治疗2、4、12周时临床评分较治疗前差异有统计学意义(P<0.05)。治疗2周时B组MG临床评分降低程度高于A组(P<0.05);4周、12周时2组比较差异无统计学意义(P>0.05);治疗12周时A、B组临床总有效率分别为81.82%、85.71%,差异无统计学意义(P>0.05)。服用他克莫司后共6例患者发生不同程度的全身/关节疼痛、恶心、腹胀、腹泻等不良反应,均经对症处理或停药后好转。2组总不良反应发生率差异无统计学意义(P=1.000)。结论:小剂量他克莫司短期内治疗难治性重症肌无力可明显改善临床症状,且不良反应发生率较低。 展开更多
关键词 重症肌无力 他克莫司 短期 疗效
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混沌优化PSO-LSSVM算法的短期负荷预测 预览
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作者 郝晓弘 刘鹏娟 汪宁渤 《兰州理工大学学报》 CAS 北大核心 2019年第1期85-90,共6页
高渗透率随机性、间歇性分布式电源的大量接入,给传统配电系统的安全、经济和可靠运行带来了一系列的问题,使得传统的负荷预测方法已不再适用.针对这一问题,提出了利用混沌优化粒子群最小二乘支持向量机(PSO-LSSVM)的算法实现对短期电... 高渗透率随机性、间歇性分布式电源的大量接入,给传统配电系统的安全、经济和可靠运行带来了一系列的问题,使得传统的负荷预测方法已不再适用.针对这一问题,提出了利用混沌优化粒子群最小二乘支持向量机(PSO-LSSVM)的算法实现对短期电力系统负荷的精确预测.利用粒子群(PSO)算法的全局搜索能力和混沌算法随机、遍历的特性,使其分别克服选参时的盲目性和寻优时粒子群(PSO)算法易出现早熟而陷入局部最优的缺点.最后在Matlab2014a软件平台上验证了混沌优化PSO-LSSVM算法的有效性和收敛性. 展开更多
关键词 智能配电网 负荷预测 短期 混沌算法 粒子群算法 最小二乘支持向量机
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Medical Knowledge Extraction and Analysis from Electronic Medical Records Using Deep Learning 预览
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作者 Peilin Li Zhenming Yuan +2 位作者 Wenbo Tu Kai Yu Dongxin Lu 《中国医学科学杂志:英文版》 CAS CSCD 2019年第2期133-139,共7页
Objectives Medical knowledge extraction (MKE) plays a key role in natural language processing (NLP) research in electronic medical records (EMR),which are the important digital carriers for recording medical activitie... Objectives Medical knowledge extraction (MKE) plays a key role in natural language processing (NLP) research in electronic medical records (EMR),which are the important digital carriers for recording medical activities of patients.Named entity recognition (NER) and medical relation extraction (MRE) are two basic tasks of MKE.This study aims to improve the recognition accuracy of these two tasks by exploring deep learning methods.Methods This study discussed and built two application scenes of bidirectional long short-term memory combined conditional random field (BiLSTM-CRF) model for NER and MRE tasks.In the data preprocessing of both tasks,a GloVe word embedding model was used to vectorize words.In the NER task,a sequence labeling strategy was used to classify each word tag by the joint probability distribution through the CRF layer.In the MRE task,the medical entity relation category was predicted by transforming the classification problem of a single entity into a sequence classification problem and linking the feature combinations between entities also through the CRF layer.Results Through the validation on the I2B2 2010 public dataset,the BiLSTM-CRF models built in this study got much better results than the baseline methods in the two tasks,where the F1-measure was up to 0.88 in NER task and 0.78 in MRE task.Moreover,the model converged faster and avoided problems such as overfitting.Conclusion This study proved the good performance of deep learning on medical knowledge extraction.It also verified the feasibility of the BiLSTM-CRF model in different application scenarios,laying the foundation for the subsequent work in the EMR field. 展开更多
关键词 MEDICAL knowledge EXTRACTION electronic MEDICAL record named ENTITY recognition MEDICAL relation EXTRACTION deep learning BIDIRECTIONAL long SHORT-TERM memory CONDITIONAL random field
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Unsupervised Electric Motor Fault Detection by Using Deep Autoencoders 预览
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作者 Emanuele Principi Damiano Rossetti +1 位作者 Stefano Squartini Francesco Piazza 《自动化学报:英文版》 CSCD 2019年第2期441-451,共11页
Fault diagnosis of electric motors is a fundamental task for production line testing, and it is usually performed by experienced human operators. In the recent years, several methods have been proposed in the literatu... Fault diagnosis of electric motors is a fundamental task for production line testing, and it is usually performed by experienced human operators. In the recent years, several methods have been proposed in the literature for detecting faults automatically. Deep neural networks have been successfully employed for this task, but, up to the authors’ knowledge, they have never been used in an unsupervised scenario. This paper proposes an unsupervised method for diagnosing faults of electric motors by using a novelty detection approach based on deep autoencoders. In the proposed method, vibration signals are acquired by using accelerometers and processed to extract LogMel coefficients as features. Autoencoders are trained by using normal data only, i.e., data that do not contain faults. Three different autoencoders architectures have been evaluated: the multilayer perceptron(MLP) autoencoder, the convolutional neural network autoencoder, and the recurrent autoencoder composed of long short-term memory(LSTM) units. The experiments have been conducted by using a dataset created by the authors, and the proposed approaches have been compared to the one-class support vector machine(OC-SVM) algorithm. The performance has been evaluated in terms area under curve(AUC) of the receiver operating characteristic curve, and the results showed that all the autoencoder-based approaches outperform the OCSVM algorithm. Moreover, the MLP autoencoder is the most performing architecture, achieving an AUC equal to 99.11 %. 展开更多
关键词 Autoencoder convolutional NEURAL NETWORKS electric motor fault DETECTION long short-term memory NEURAL NETWORKS NOVELTY DETECTION
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中青年阻塞性睡眠呼吸暂停低通气综合征患者注意力及短期记忆损伤的研究
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作者 李琪 李宁真 +3 位作者 李婷婷 孙彦秋 王婧 陈锐 《中华结核和呼吸杂志》 CAS CSCD 北大核心 2019年第6期419-425,共7页
目的探索中青年阻塞性睡眠呼吸暂停低通气综合征(OSAHS)患者注意力及短期记忆损害特征及影响因素。方法选择2016年7月至2017年7月于苏州大学附属第二医院睡眠门诊因打鼾而就诊的中青年患者,纳入OSAHS患者151例和非OSAHS者52例,对所有20... 目的探索中青年阻塞性睡眠呼吸暂停低通气综合征(OSAHS)患者注意力及短期记忆损害特征及影响因素。方法选择2016年7月至2017年7月于苏州大学附属第二医院睡眠门诊因打鼾而就诊的中青年患者,纳入OSAHS患者151例和非OSAHS者52例,对所有203例受试者行多导睡眠图(PSG)监测,记录睡眠参数及呼吸参数。据睡眠呼吸暂停低通气指数(AHI)将患者分为3组:非OSAHS组(0次/h<AHI≤5次/h)、轻中度OSAHS组(5次/h<AHI≤30次/h)及重度OSAHS组(AHI>30次/h),行嗜睡、总体认知评估及注意力、短期记忆检测(连线测试、数字广度测试、复杂图形测试)。比较3组患者PSG参数、总体认知功能及注意力、短期记忆之间的差异,并探讨中青年OSAHS患者注意力、短期记忆损伤的特点及影响因素。结果(1)总体认知功能评估:重度组OSAHS患者MoCA评分为27.0(25.0, 28.0),低于非OSAHS组[27.0(26.0, 28.0)]与轻中度OSAHS组[27.0(26.0, 27.0)],差异有统计学意义(P<0.01);(2)主观嗜睡程度评估:重度组OSAHS患者ESS得分(11.4±5.4)高于非OSAHS组(5.3±4.5)与轻中度OSAHS组(8.0±5.0),差异有统计学意义(P<0.01);(3)注意力比较:重度OSAHS组、非OSAHS组和轻中度OSAHS组数字广度测试顺背得分(分别为8.1±1.1、8.8±0.9和8.5±1.0)、倒背得分[分别为5.5(4.0, 7.0)、6.0(5.0, 7.0)和6.0(5.0, 7.0)],差异均有统计学意义(P<0.01);(4)记忆力比较:重度OSAHS组、非OSAHS组和轻中度OSAHS组复杂图形再绘得分分别为23.0(16.0, 27.0)、26.0(24.0, 28.0)和24.0(20.0, 28.0),差异有统计学意义(P<0.01);(5)执行功能比较:重度OSAHS组、非OSAHS组和轻中度OSAHS组连线测试A使用时间分别为46.7±19.0、40.2±17.4和34.6±17.2、B使用时间分别为76.9±32.6、67.2±21.2和58.6±27.5,差异均有统计学意义(P<0.01)。经多元Logistic逐步回归分析得出,AHI、ODI、NREM(Ⅰ+Ⅱ)期比率是影响OSAHS患者注意力及短期记忆的独立因素。结论中青年OSAHS患者注意力、 展开更多
关键词 睡眠呼吸暂停 阻塞性 睡眠分期 注意力 记忆 短时
The Impact of Meteorological Factors on the Short-term Cumulative Effect of Air Particulate in Tianjin 预览
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作者 Wang Wei Liu Lili Wang Yan 《气象与环境研究:英文版》 CAS 2019年第2期27-32,40共7页
In order to reveal the rapid increase mechanism of particulate concentration in short time,a notion of short-term cumulative effect of air particulate is defined as the significant increase of pollutant concentration ... In order to reveal the rapid increase mechanism of particulate concentration in short time,a notion of short-term cumulative effect of air particulate is defined as the significant increase of pollutant concentration in a short time under the condition of breeze,stable weather and constant emission caused by human being’s activities. Subsequently,an index of short-term cumulative effect is established with air diffusive equation,and then the macro-scale meteorological situation and micro-scale factors of forming the short-term cumulative effect are discussed with the observation data. The macro-scale meteorological variables contain upper-level weather situations and surface weather situations. The micro-scale factors mainly include the boundary-layer height and boundary-layer stability. The analyses show that boundary-layer factors and weather variables have a significant influence on the short-term cumulative effect. The notion of short-term cumulative effect will play an important role in interpreting the severe pollution weather. 展开更多
关键词 AIR PARTICULATE SHORT-TERM CUMULATIVE Effect METEOROLOGICAL factor CUMULATIVE index
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水电富集电网大规模水电站群短期实用化调度方法
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作者 申建建 张秀飞 +4 位作者 曹瑞 程春田 李秀峰 吴洋 周彬彬 《中国电机工程学报》 EI CSCD 北大核心 2019年第10期2816-2827,共12页
超大规模水电站群优化调度"维数灾"和结果实用性问题是水电和电网运行面临的重大理论和实践难题。该文以我国西南水电富集电网百座级水电系统为工程背景,提出考虑调度特征降维的水电短期实用化调度方法。结合系统层级、空间... 超大规模水电站群优化调度"维数灾"和结果实用性问题是水电和电网运行面临的重大理论和实践难题。该文以我国西南水电富集电网百座级水电系统为工程背景,提出考虑调度特征降维的水电短期实用化调度方法。结合系统层级、空间属性、任务要求、计划特殊性等调度特征进行水电站分类分组降维求解,提出基于调峰响应的弃水修正策略和低谷时段负荷均衡削减策略,实现固定调度方式电站的校核分析与出力调整;针对中小流域梯级水电站,以总出力过程为控制条件,以总耗水最小为目标,优化梯级电站间负荷分配;针对大型流域梯级和主要水电站,构建调峰调度模型,提出平衡电站等负荷率调度方法,实现系统调峰响应和全时段负荷平衡。通过云南电网162座水电站日前计划编制实例验证,该方法能够快速给出合理的水电调度结果,满足电网实际运行的时效性和实用性要求。 展开更多
关键词 水电富集电网 水电站群 短期 降维 调度特征
短时低氧处理后表皮细胞差异表达基因及相关通路分析 预览
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作者 燕荣帅 周鑫 +2 位作者 陈鑫 樊东力 张一鸣 《中华细胞与干细胞杂志(电子版)》 2019年第2期86-91,共6页
目的探讨短时低氧处理后表皮细胞HaCaT 转录组差异并找出低氧微环境下表皮细胞关键调控基因。方法本研究分低氧组和常氧对照组,低氧组在1 ﹪浓度低氧孵箱中培养30 min,常氧组在常规孵箱中培养30 min,其后采用Trizol 法提取总RNA,采用基... 目的探讨短时低氧处理后表皮细胞HaCaT 转录组差异并找出低氧微环境下表皮细胞关键调控基因。方法本研究分低氧组和常氧对照组,低氧组在1 ﹪浓度低氧孵箱中培养30 min,常氧组在常规孵箱中培养30 min,其后采用Trizol 法提取总RNA,采用基因芯片技术筛选差异基因,进一步对差异基因采用GO 及KEGG Pathway 分析关键调控基因。同时采用qRT-PCR 对结果进行验证。结果与对照组相比,低氧微环境处理后表皮细胞上调基因5 416个,下调基因5 060 个;GO 及KEGG Pathway 分析显示差异基因涉及氧化应激、免疫应答、转录因子调控、细胞迁移、信号转导通路及趋化性等。进一步的分析发现,显著调控的基因DDIT3、CCL20 以及IL6 基因在低氧调控中起着重要作用。同时qRT-PCR 验证结果与芯片结果一致。结论低氧微环境下表皮细胞除氧化应激外,细胞迁移相关基因扮演着重要作用,同时发现表皮细胞能上调基因CCL20 以及IL6、下调基因DDIT3 在大部分调控中均发挥着重要作用,这些分子对揭示表皮细胞迁移调控及创面愈合机理具有重要的研究价值。 展开更多
关键词 表皮细胞 短时 低氧 基因芯片 关键基因
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短期经颅磁治疗配合康复训练治疗儿童孤独症谱系障碍的临床研究 预览
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作者 李杰 李之林 +5 位作者 李新剑 吴野 武改 鲍克秀 孟露露 杨忠秀 《徐州医科大学学报》 CAS 2019年第3期195-197,共3页
目的探讨短期经颅磁治疗配合康复训练对儿童孤独症谱系障碍的临床疗效。方法将60例孤独症谱系障碍患儿分为经颅磁治疗组和对照组,每组30例。经颅磁治疗组采用为期10d短期经颅磁治疗配合康复训练,对照组仅行康复训练。治疗前和治疗10d后... 目的探讨短期经颅磁治疗配合康复训练对儿童孤独症谱系障碍的临床疗效。方法将60例孤独症谱系障碍患儿分为经颅磁治疗组和对照组,每组30例。经颅磁治疗组采用为期10d短期经颅磁治疗配合康复训练,对照组仅行康复训练。治疗前和治疗10d后,使用孤独症治疗评估量表(Autism Treatment Evaluation Checklist,ATEC)评估其对孤独症谱系障碍的疗效。结果治疗10d后,经颅磁治疗组ATEC总评分、感知功能评分、健康和行为评分均较治疗前明显降低(P<0.05或P<0.01);对照组患儿治疗10d后ATEC总评分、感知功能评分、健康和行为评分与治疗前相比无明显变化(P>0.05)。结论短期康复训练不能明显改善儿童孤独症谱系障碍,而短期经颅磁治疗配合康复训练可改善儿童孤独症谱系障碍,尤其是感知功能、健康和行为。 展开更多
关键词 孤独症谱系障碍 经颅磁治疗 短期 孤独症治疗评估量表 行为
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船舶横向运动短期姿态预报数学建模可行性研究 预览
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作者 潘宝柱 魏文英 马艳秀 《舰船科学技术》 北大核心 2019年第10期10-12,共3页
传统的船舶横向运动短期姿态预报数学模型存在着预报性能低的缺陷,为此提出船舶横向运动短期姿态预报数学建模可行性研究。采用平均滤除法对船舶横向运动数据中的不良数据进行去除,完成船舶横向运动数据准备,将得到的船舶横向运动数据... 传统的船舶横向运动短期姿态预报数学模型存在着预报性能低的缺陷,为此提出船舶横向运动短期姿态预报数学建模可行性研究。采用平均滤除法对船舶横向运动数据中的不良数据进行去除,完成船舶横向运动数据准备,将得到的船舶横向运动数据进行归一化处理,适应预报函数的需求,将得到的归一化的船舶横向运动数据输入到BP神经网络算法中完成船舶横向运动短期姿态的预报,实现了船舶横向运动短期姿态预报数学模型的建立。通过实验得到,构建的船舶横向运动短期姿态预报数学模型预报误差比传统模型低了21.41%,预报时间比传统模型高出3.25 s,充分说明构建的船舶横向运动短期姿态预报数学模型具备良好的可行性与预报性能。 展开更多
关键词 船舶横向运动 短期 姿态预报 数学模型
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Prediction of short-term mortality after valve surgery
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作者 Liu-Jia-Zi Shao Fu-Shan Xue +1 位作者 Rui-Juan Guo Li Zheng 《中华医学杂志:英文版》 SCIE CAS CSCD 2019年第5期624-625,共2页
To the Editor: In a single-center perspective study by Chen et al[1] determining the risk factors and predictors of shortterm mortality after valve surgery, multivariate logistic regression analysis showed that pre-op... To the Editor: In a single-center perspective study by Chen et al[1] determining the risk factors and predictors of shortterm mortality after valve surgery, multivariate logistic regression analysis showed that pre-operative New York Heart Association functional class 4. 展开更多
关键词 SHORT-TERM MORTALITY VALVE SURGERY RISK FACTORS
Improved Social Emotion Optimization Algorithm for Short-Term Traffic Flow Forecasting Based on Back-Propagation Neural Network
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作者 张军 赵申卫 +1 位作者 王远强 朱新山 《上海交通大学学报:英文版》 EI 2019年第2期209-219,共11页
The back-propagation neural network(BPNN) is a well-known multi-layer feed-forward neural network which is trained by the error reverse propagation algorithm. It is very suitable for the complex of short-term traffic ... The back-propagation neural network(BPNN) is a well-known multi-layer feed-forward neural network which is trained by the error reverse propagation algorithm. It is very suitable for the complex of short-term traffic flow forecasting;however, BPNN is easy to fall into local optimum and slow convergence. In order to overcome these deficiencies, a new approach called social emotion optimization algorithm(SEOA) is proposed in this paper to optimize the linked weights and thresholds of BPNN. Each individual in SEOA represents a BPNN. The availability of the proposed forecasting models is proved with the actual traffic flow data of the 2 nd Ring Road of Beijing. Experiment of results show that the forecasting accuracy of SEOA is improved obviously as compared with the accuracy of particle swarm optimization back-propagation(PSOBP) and simulated annealing particle swarm optimization back-propagation(SAPSOBP) models. Furthermore, since SEOA does not respond to the negative feedback information, Metropolis rule is proposed to give consideration to both positive and negative feedback information and diversify the adjustment methods. The modified BPNN model, in comparison with social emotion optimization back-propagation(SEOBP) model, is more advantageous to search the global optimal solution. The accuracy of Metropolis rule social emotion optimization back-propagation(MRSEOBP) model is improved about 19.54% as compared with that of SEOBP model in predicting the dramatically changing data. 展开更多
关键词 urban TRAFFIC short-term TRAFFIC flow forecasting social EMOTION optimization algorithm(SEOA) BACK-PROPAGATION neural network(BPNN) METROPOLIS rule
Video Description with Integrated Visual and Textual Information 预览
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作者 Yue Wang Jinlai Liu Xiaojie Wang 《中国通信:英文版》 SCIE CSCD 2019年第1期119-128,共10页
Video Description aims to automatically generate descriptive natural language for videos.Due to the large volume of multi-modal data and successful implementations of Deep Neural Networks(DNNs),a wide range of models ... Video Description aims to automatically generate descriptive natural language for videos.Due to the large volume of multi-modal data and successful implementations of Deep Neural Networks(DNNs),a wide range of models have been proposed.However,previous models learn insufficient linguistic information or correlation between visual and textual modalities.In order to address those problems,this paper proposes an integrated model using Long Short-Term Memory(LSTM).This proposed model consists of triple channels in parallel:a primary video description channel,a sentence-to-sentence channel for language learning,and a channel to integrate visual and textual information.Additionally,the parallel three channels are connected by LSTM weight matrices during training.The VD-ivt model is evaluated on two publicly available datasets,i.e.Youtube2Text and LSMDC.Experimental results demonstrate that the performance of the proposed model outperforms those benchmarks. 展开更多
关键词 VIDEO description(VD) deep NEURAL network(DNN) convolutional NEURAL network(CNN) long short-term memory(LSTM)
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风湿性心瓣膜病所致顽固性心力衰竭短期应用血液透析治疗的研究 预览
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作者 李晓丹 《中国医药科学》 2019年第7期212-214,235共4页
目的对风湿性心瓣膜病所致顽固性心力衰竭短期应用血液透析治疗的研究进行分析。方法选取2016年7月~2018年4月期间收治的42例风湿性心瓣膜病所致顽固性心力衰竭患者作为本次研究对象,随机分为对照组(n=21)与观察组(n=21),对照组施以内... 目的对风湿性心瓣膜病所致顽固性心力衰竭短期应用血液透析治疗的研究进行分析。方法选取2016年7月~2018年4月期间收治的42例风湿性心瓣膜病所致顽固性心力衰竭患者作为本次研究对象,随机分为对照组(n=21)与观察组(n=21),对照组施以内科药物治疗,观察组采用血液透析治疗。对两组患者治疗结果进行比较。结果两组患者治疗前生化、内分泌指标比较,差异无统计学意义(P>0.05)。治疗后观察组患者生化指标、内分泌指标、死亡情况均优于对照组,差异有统计学意义(P<0.05)。结论在风湿性心瓣膜病所致顽固性心力衰竭患者中应用短期血液透析治疗具有显著效果,可改善患者指标,降低死亡率,值得推广。 展开更多
关键词 风湿性心瓣膜病 顽固性心力衰竭 短期 血液透析
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DC-CIK细胞生物疗法联合化疗治疗中晚期非小细胞肺癌的近期临床效果研究
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作者 张霞 《中国实用乡村医生杂志》 2019年第3期57-60,共4页
目的探讨DC-CIK细胞生物联合常规化疗治疗中晚期非小细胞肺癌的近期临床效果。方法选取2014年1月-2015年6月大连市第五人民医院收治的86例非小细胞肺癌患者,依据治疗方案的不同将患者分为对照组和观察组各43例。对照组应用常规化疗方案... 目的探讨DC-CIK细胞生物联合常规化疗治疗中晚期非小细胞肺癌的近期临床效果。方法选取2014年1月-2015年6月大连市第五人民医院收治的86例非小细胞肺癌患者,依据治疗方案的不同将患者分为对照组和观察组各43例。对照组应用常规化疗方案,观察组在常规化疗方案基础上联合应用DC-CIK细胞生物疗法。对比两组患者的近期临床效果,治疗前后血清肿瘤标志物、免疫功能指标及用药期间的不良反应发生情况。结果治疗后观察组总有效率为53.5%高于对照组的30.2%,差异具有统计学意义(χ^2=4.778,P<0.05)。治疗后两组TNF-α、CD4+、CD4+/CD8+水平均有所改善,且观察组改善程度优于对照组,差异具有统计学意义(t值分别为4.378,5.095和4.336,P值均<0.05)。治疗期间不良反应发生率观察组39.53%、对照组34.88%,观察组率略高于对照组但差异无统计学意义(χ^2=0.199,P〉0.05)。结论DC-CIK细胞生物疗法联合常规化疗治疗非小细胞肺癌的近期疗效优于单纯化疗,能够改善患者免疫水平,且不会增加不良反应,具有较好临床应用价值。 展开更多
关键词 肺癌 非小细胞 化疗 生物疗法 DGCIK细胞 疗效 近期
伴视空间工作记忆障碍的早期帕金森病18F-FDG PET显像脑葡萄糖代谢特点 被引量:1
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作者 李修明 刘丰韬 +1 位作者 张宇燕 谭海波 《中华核医学与分子影像杂志》 CAS 北大核心 2019年第1期10-14,共5页
目的用18F-脱氧葡萄糖(FDG)PET显像研究伴有视空间工作记忆障碍的早期帕金森病(PD)患者脑葡萄糖代谢特点。方法研究对象为2015年1月至2017年3月的早期PD患者[伴视空间工作记忆障碍组,男14例,女6例,年龄(55.7±6.7)岁;无视空间工作... 目的用18F-脱氧葡萄糖(FDG)PET显像研究伴有视空间工作记忆障碍的早期帕金森病(PD)患者脑葡萄糖代谢特点。方法研究对象为2015年1月至2017年3月的早期PD患者[伴视空间工作记忆障碍组,男14例,女6例,年龄(55.7±6.7)岁;无视空间工作记忆障碍组,男13例,女7例,年龄(55.7±8.5)岁]及健康对照[男14名,女6名,年龄(54.6±6.4)岁]。受试者均行18F-FDGPET显像,获得脑葡萄糖代谢图像。应用统计参数图(SPM)进行数据分析,比较各组脑葡萄糖代谢变化的差异和特点。结果与健康对照组比较,早期PD患者在壳核、苍白球、丘脑、脑桥、小脑和初级运动皮质区均表现为葡萄糖代谢明显增强,而枕叶及颞叶部分脑区代谢减低(Zmax:3.19~6.86,t:2.11~9.96,均P<0.001)。有视空间工作记忆障碍早期PD患者与无视空间工作记忆障碍患者相比,出现了双侧背外侧额前回、双侧后顶叶等视觉处理中枢葡萄糖代谢减低区。结论伴视空间工作记忆障碍的早期PD患者脑内视觉通道葡萄糖代谢异常可能是其视空间工作记忆障碍的原因之一。 展开更多
关键词 帕金森病 视觉障碍 记忆障碍 记忆 短时 正电子发射断层显像术 脱氧葡萄糖
Forecasting of Short-term Load based on LMD and BBO-RBF Model 预览
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作者 HOU Luting GAO Junwei 《国际设备工程与管理:英文版》 2019年第2期101-108,共8页
Short-term load forecasting is a basis of power system dispatching and operation. In order to improve the short term power load precision, a novel approach for short-term load forecasting is presented based on local m... Short-term load forecasting is a basis of power system dispatching and operation. In order to improve the short term power load precision, a novel approach for short-term load forecasting is presented based on local mean decomposition (LMD) and the radial basis function neural network method (RBFNN). Firstly, the decomposition of LMD method based on characteristics of load data then the decomposed data are respectively predicted by using the RBF network model and predicted by using the BBO-RBF network model. The simulation results show that the RBF network model optimized by using BBO algorithm is optimized in error performance index, and the prediction accuracy is higher and more effective. 展开更多
关键词 SHORT-TERM load local mean DECOMPOSITION RADIAL BASIS function NEURAL network BBO algorithm
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