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基于RE-AIM和柯氏模型的反思实践培训方案在本科医学带教中的应用
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作者 魏锦来 方敏 陈婷婷 《中国继续医学教育》 2024年第16期122-126,共5页
目的观察基于可及性、有效性、采用率、实施性与持续性(reach,effectiveness,adoption,implementation,maintenance,RE-AIM)和柯氏模型的反思实践培训方案在本科医学带教中的应用效果。方法选取2022年3月-2023年6月重庆医科大学附属第... 目的观察基于可及性、有效性、采用率、实施性与持续性(reach,effectiveness,adoption,implementation,maintenance,RE-AIM)和柯氏模型的反思实践培训方案在本科医学带教中的应用效果。方法选取2022年3月-2023年6月重庆医科大学附属第一医医学临床医学专业学生124名,使用随机数字表法将其分为对照组(n=61)及研究组(n=63)。对照组采用传统教学方案,研究组使用基于RE-AIM和柯氏模型的反思实践培训方案进行教学。观察2组学生的教学效果、考核成绩、自我效能、批判思维评分及学生满意度。结果研究组临床思维能力、医学人文精神、公共卫生服务、社区情怀评分均高于对照组;研究组实践成绩、理论成绩、总分高于对照组;研究组工作职责评分、教育要求评分高于对照组;研究组寻找真相、自信心、求知欲、分析能力、开放思维、认知成熟度、系统化能力7个维度均高于对照组;研究组学习兴趣激发、思维能力提高、自学能力培养、理论知识掌握、语言和表达能力提高5个维度满意度评分高于对照组,差异均有统计学意义(P<0.05)。结论基于RE-AIM和柯氏模型的反思实践培训方案有助于提高本科医学生的教学效果,提高教理论及实践成绩,培养实习生批判思维并提高其对带教工作的满意。 展开更多
关键词 RE-aim 柯氏模型 反思实践 教学方案 本科 医学带教 批判思维
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HDAC3抑制剂RGFP966通过下调TGF-β1/SMAD3/STAT-1信号通路抑制AIM2炎症小体活化和EMT缓解子宫内膜纤维化
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作者 卢建军 张新悦 《医学分子生物学杂志》 CAS 2024年第3期211-216,共6页
目的探讨HDAC3抑制剂RGFP966缓解子宫内膜纤维化的分子机制。方法将18只6~8周雌性SD大鼠随机分为3组,Control组、IUA模型组(即宫内粘连大鼠模型组)、RGFP966治疗组(IUA模型组给予HDAC3抑制剂RGFP966治疗),每组6只。建立IUA大鼠模型。EL... 目的探讨HDAC3抑制剂RGFP966缓解子宫内膜纤维化的分子机制。方法将18只6~8周雌性SD大鼠随机分为3组,Control组、IUA模型组(即宫内粘连大鼠模型组)、RGFP966治疗组(IUA模型组给予HDAC3抑制剂RGFP966治疗),每组6只。建立IUA大鼠模型。ELISA测定大鼠血清炎症因子TNF-α、IL-1β和IL-6水平。qPCR法测定大鼠子宫内膜组织上皮间质转化标志物E-cadherin、N-cadherin、α-SMA、Vimentin mRNA相对表达水平。蛋白质印迹法测定大鼠子宫内膜组织TGF-β1、SMAD3、p-STAT-1、STAT-1、AIM2、IL-18、cleaved-IL-1β、IL-1β的表达水平。结果与Control组相比,IUA模型组大鼠子宫角壁变薄,血清炎症因子TNF-α、IL-1β、IL-6水平升高(P<0.05);E-cadherin mRNA相对表达水平降低,N-cadherin、α-SMA、Vimentin mRNA相对表达水平升高(P<0.05);TGF-β1、SMAD3、p-STAT-1蛋白质表达水平增强(P<0.05);AIM2、IL-18、cleaved-IL-1β的表达水平增强(P<0.05)。与IUA模型组相比,RGFP966治疗组部分逆转(P<0.05)了上述指标。STAT-1和IL-1β的表达水平在上述3个分组中无明显差异(P>0.05)。结论HDAC3的抑制剂RGFP966可通过下调TGF-β1/SMAD3/STAT-1信号通路抑制AIM2炎症小体和EMT,缓解子宫内膜纤维化。 展开更多
关键词 子宫内膜纤维化 宫内粘连 HDAC3抑制剂RGFP966 TGF-β1/SMAD3/STAT-1信号通路 aim2炎症小体
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雷神基于AIM 9X的DIRCM系统研究
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作者 武伟 李建征 +1 位作者 姜成舟 潘国庆 《激光与红外》 CAS CSCD 北大核心 2024年第3期336-339,共4页
以便携式防空系统(MANPADS)为典型代表的红外精确制导武器给军用和民用飞机带来巨大的威胁。目前最行之有效应对热寻的制导武器的方法便是以红外波段激光作为光源的定向红外干扰系统。本文主要介绍了美国雷神公司如何基于现有的AIM-9X... 以便携式防空系统(MANPADS)为典型代表的红外精确制导武器给军用和民用飞机带来巨大的威胁。目前最行之有效应对热寻的制导武器的方法便是以红外波段激光作为光源的定向红外干扰系统。本文主要介绍了美国雷神公司如何基于现有的AIM-9X导引头技术开发新一代定向红外对抗系统,该系统具备高效、可靠、紧凑、重量轻且价格低廉等诸多优点,并且通过功能扩展可以轻松应对从紫外到中红外等多种波段导弹威胁。 展开更多
关键词 aim9X 定向红外对抗 激光指示系统
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外周血单个核细胞AIM2炎症小体激活释放白细胞介素-18介导带状疱疹的临床研究 被引量:1
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作者 陈泽豪 王景 +3 位作者 高翔宇 蒋昌宇 李陈广 肖礼祖 《中国疼痛医学杂志》 CAS CSCD 北大核心 2024年第5期348-355,共8页
目的:探索在带状疱疹病人不同时期的外周血单个核细胞(peripheral blood mononuclear cell,PBMC)中AIM2炎症小体的活化和释放白细胞介素-18(interleukin-18,IL-18)情况并进行初步验证。方法:收集并分离华中科技大学协和深圳医院疼痛科2... 目的:探索在带状疱疹病人不同时期的外周血单个核细胞(peripheral blood mononuclear cell,PBMC)中AIM2炎症小体的活化和释放白细胞介素-18(interleukin-18,IL-18)情况并进行初步验证。方法:收集并分离华中科技大学协和深圳医院疼痛科2022年4月至2024年1月67名急性期带状疱疹神经痛(acute herpetic neuralgia,AHN)、58名亚急性期带状疱疹神经痛(subacute herpetic neuralgia,SHN)、38名带状疱疹后神经痛(post herpetic neuralgia,PHN)病人及30名健康对照者的外周血单个核细胞和血清。通过实时荧光定量PCR、蛋白质免疫印迹法及蛋白质芯片技术检测黑色素瘤缺乏因子2(absent in melanoma 2,AIM2)炎症小体相关基因和蛋白的表达情况。结果:在基因表达和蛋白质水平上与健康对照者相比,AIM2和IL-18的基因表达在带状疱疹不同时期均显著上升(P<0.05),且在PHN期差异尤为明显(P<0.001)。GSDMD蛋白被切割活化,产生具有细胞膜成孔活性的GSDMD-NT片段,诱导细胞焦亡。不同带状疱疹时期病人血清中IL-18的分泌水平明显升高,尤其在PHN时期,上升最为显著。结论:外周血单个核细胞中AIM2炎症小体激活,释放的IL-18参与带状疱疹疾病的发生发展过程。 展开更多
关键词 带状疱疹 aim2炎症小体 白细胞介素-18 细胞焦亡 外周血单个核细胞
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CD147通过AIM2炎症小体介导宫颈癌细胞焦亡和增殖
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作者 王玲 秦祥川 +1 位作者 李金秋 阿仙姑·哈斯木 《昆明医科大学学报》 CAS 2024年第1期15-21,共7页
目的 探讨跨膜蛋白CD147表达量变化对AIM2炎症小体介导的宫颈癌细胞焦亡及增殖的影响。方法 采用Western blot实验检测CD147在宫颈癌细胞SiHa(HPV+)、C33a(HPV-)和正常宫颈上皮细胞H8(HPV+)、HCer Epic(HPV-)中的表达水平;通过慢病毒转... 目的 探讨跨膜蛋白CD147表达量变化对AIM2炎症小体介导的宫颈癌细胞焦亡及增殖的影响。方法 采用Western blot实验检测CD147在宫颈癌细胞SiHa(HPV+)、C33a(HPV-)和正常宫颈上皮细胞H8(HPV+)、HCer Epic(HPV-)中的表达水平;通过慢病毒转染SiHa细胞下调CD147的表达,根据不同处理分为SiHa组、阴性对照组(shCD147-NON)、敲低组1(shCD147-1)和敲低组2(shCD147-2),通过Western blot、RT-qPCR和观察细胞绿色荧光表达验证转染效果;通过Western blot和RT-qPCR检测CD147和AIM2炎症小体相关因子AIM2、Caspase-1、IL-18、GSDMD蛋白和mRNA的表达;检测细胞培养上清中乳酸脱氢酶(LDH)释放度,荧光倒置显微镜下观察细胞的形态;CCK-8实验检测细胞的增殖能力;细胞克隆实验检测细胞集落形成能力。结果 Western blot结果显示,与HCerEpic细胞比较,SiHa细胞中CD147蛋白表达最高(P <0.05);CD147低表达慢病毒有效下调了SiHa细胞CD147表达水平(P <0.05);Western blot及RT-qPCR实验结果表明,与SiHa组相比,shCD147-1组和shCD147-2组AIM2、Caspase-1、IL-18、GSDMD蛋白和mRNA表达明显升高(P <0.05);乳酸脱氢酶(LDH)释放实验显示,与SiHa组相比,shCD147组LDH释放度明显升高(P <0.05);荧光倒置显微镜下显示,shCD147组出现肿胀和空泡化,表现出典型的细胞焦亡现象;与SiHa组相比,shCD147-1组和shCD147-2组细胞增殖能力和集落形成能力明显降低(P <0.05)。结论 CD147低表达有效上调宫颈癌SiHa细胞AIM2炎症相关因子的表达,诱发细胞焦亡,抑制细胞的增殖和克隆。 展开更多
关键词 宫颈癌 CD147 aim2炎症小体 细胞焦亡 增殖
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血小板-白蛋白-胆红素指数(PALBI)联合AIMS65评分对肝硬化并发急性上消化道出血患者短期预后的预测价值 被引量:2
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作者 戴天骄 李静 《临床肝胆病杂志》 CAS 北大核心 2024年第2期298-305,共8页
目的探讨血小板-白蛋白-胆红素指数(PALBI)联合AIMS65评分对肝硬化并发急性上消化道出血(AUGIB)患者入院后6周内再出血及死亡的预测价值。方法选取2021年2月—2022年10月在锦州医科大学附属第一医院住院治疗的肝硬化并发AUGIB患者238例... 目的探讨血小板-白蛋白-胆红素指数(PALBI)联合AIMS65评分对肝硬化并发急性上消化道出血(AUGIB)患者入院后6周内再出血及死亡的预测价值。方法选取2021年2月—2022年10月在锦州医科大学附属第一医院住院治疗的肝硬化并发AUGIB患者238例,所有纳入患者均随访6周,根据预后情况分为死亡组(n=65)和生存组(n=173)、未再出血组(n=149)和再出血组(n=89)。收集患者的一般资料及实验室指标(血常规,肝、肾功能及凝血指标等),计算入院时的PALBI评分、AIMS65评分、Child-Turcotte-Pugh(CTP)评分、终末期肝病模型(MELD)评分。计量资料两组间比较采用成组t检验或Mann-Whitney U检验;计数资料两组间比较采用χ2检验。采用多因素Logistic回归模型分析肝硬化并发AUGIB患者入院治疗后6周内死亡或再出血的危险因素。通过受试者工作特征曲线(ROC曲线)及曲线下面积(AUC)评估各评分系统的预测效能;AUC的比较采用DeLong检验。结果死亡组和生存组患者比较,呕血、既往有静脉曲张病史、Alb、TBil、INR、Cr、PT、收缩压、PALBI评分、AIMS65评分、CTP评分和MELD评分差异均有统计学意义(P值均<0.05);多因素Logistic回归分析结果显示,呕血(OR=4.34,95%CI:1.88~10.05,P<0.001)、既往有静脉曲张病史(OR=3.51,95%CI:1.37~8.98,P=0.009)、PALBI评分(OR=4.49,95%CI:1.48~13.64,P=0.008)及AIMS65评分(OR=3.85,95%CI:2.35~6.30,P<0.001)是患者死亡的独立危险因素;各评分预测生存情况的ROC曲线结果显示,CTP评分、MELD评分、PALBI评分、AIMS65评分、PALBI联合AIMS65评分的AUC分别为0.758、0.798、0.789、0.870、0.888,其中PALBI联合AIMS65评分的AUC明显高于4种评分单独预测的AUC(P值均<0.05)。再出血组和未再出血组患者比较,呕血、糖尿病病史、Alb、TBil、INR、Cr、PT、PALBI评分、AIMS65评分、CTP评分和MELD评分差异均有统计学意义(P值均<0.05);多因素Logistic回归分析结果显示,PALBI评分(OR=2.41,95%CI:1.17~4.95,P=0.017)和AIMS65评分(OR=1.58,95%CI:1.17~2.15,P=0.003)是患者再出血的独立危险因素;各评分预测再出血的ROC曲线结果显示,CTP评分、MELD评分、PALBI评分、AIMS65评分、PALBI联合AIMS65评分的AUC分别为0.680、0.719、0.709、0.711、0.741,PALBI联合AIMS65评分的AUC最大(P值均<0.05),但特异度较低。结论PALBI评分联合AIMS65评分对肝硬化并发AUGIB患者入院后6周内的死亡具有一定的预测价值,优于CTP评分及MELD评分单独检测;对6周内再出血预测价值较低,准确性一般。 展开更多
关键词 肝硬化 急性上消化道出血 PALBI评分 aimS65评分 预后
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A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction 被引量:1
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作者 Fei Ye Yunbin Yuan 《Geodesy and Geodynamics》 EI CSCD 2024年第1期100-105,共6页
Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currentl... Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods. 展开更多
关键词 Stochastic model LS+AR short-term prediction The earth rotation parameter(ERP) Observation model
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术前Glasgow-Blatchford和AIMS65评分对介入治疗非静脉曲张性上消化道出血患者的预后评估
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作者 张炜 徐珉杰 +2 位作者 潘龙 袁逸枫 韩世龙 《介入放射学杂志》 CSCD 北大核心 2024年第9期1005-1008,共4页
目的 探讨Glasgow-Blatchford(GBS)和AIMS65术前评分对非静脉曲张性上消化道出血患者介入治疗预后的评估作用。方法 收集2018年至2021年在上海市第十人民医院介入血管外科接受经导管动脉栓塞(TAE)治疗的59例因非静脉曲张性上消化道出血... 目的 探讨Glasgow-Blatchford(GBS)和AIMS65术前评分对非静脉曲张性上消化道出血患者介入治疗预后的评估作用。方法 收集2018年至2021年在上海市第十人民医院介入血管外科接受经导管动脉栓塞(TAE)治疗的59例因非静脉曲张性上消化道出血患者相关临床信息。观察患者术前GBS及AIMS65评分对术后结局的预测作用。结果 随着GBS及AIMS65术前评分数值增高,患者的病死概率越高;相比AIMS65(AUC=0.630,95%CI:0.494~0.752),GBS对于非静脉曲张性上消化道出血患者术后住院死亡结局预测价值较高(AUC=0.823,95%CI:0.702~0.910);GBS截断值>9分时,预测患者住院死亡的约登指数为0.54。结论 GBS术前评分对非静脉曲张性上消化道出血患者术后住院死亡发生的预测价值较AIMS65更高。 展开更多
关键词 Glasgow-Blatchford评分 aimS65评分 非静脉曲张性上消化道出血 经导管动脉栓塞
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AIM在炎症反应和脂质代谢疾病中的作用
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作者 张帆 田春雨 +4 位作者 王景存 喇孝瑾 付茜茹 李洁 付文浩 《中国比较医学杂志》 CAS 北大核心 2024年第3期142-148,共7页
巨噬细胞凋亡抑制因子(apoptosis inhibitor of macrophage,AIM),是清道夫受体富含半胱氨酸残基超家族(scavenger receptor cysteine rich-super family,SRCR-SF)B组的成员之一。AIM为巨噬细胞分泌的一种可溶性蛋白,该蛋白的表达受肝X受... 巨噬细胞凋亡抑制因子(apoptosis inhibitor of macrophage,AIM),是清道夫受体富含半胱氨酸残基超家族(scavenger receptor cysteine rich-super family,SRCR-SF)B组的成员之一。AIM为巨噬细胞分泌的一种可溶性蛋白,该蛋白的表达受肝X受体(liver X receptor,LXR)控制,且在机体的免疫反应中起重要作用。AIM作为巨噬细胞的一种分泌蛋白,发挥着广泛的作用,不仅对巨噬细胞的凋亡具有抑制作用,并且可参与调控巨噬细胞极化。还有相关研究发现,AIM参与炎症、肥胖、动脉粥样硬化和癌症等多种生理、病理过程;可以作为结核病和肝硬化等疾病的生物诊断标志物;可以通过抑制脂肪酸合成酶(fatty acid synthase,FAS)活性从而促进脂肪细胞的脂解,在调节脂质内稳态平衡、脂质代谢与自身免疫疾病中发挥着重要的作用。该文论述了AIM的分子特征及其在炎症反应和脂质代谢等相关疾病方面的作用,展示AIM的多种功能特点,为相关的医学研究提供依据。 展开更多
关键词 aim 炎症反应 脂质代谢
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AIMS系统终端显示不一致分析
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作者 宋伟 李春菊 马少东 《工业控制计算机》 2024年第2期36-37,40,共3页
在航班信息处理系统(AIMS)各终端数据显示不一致的情况下寻找该问题的解决方法。以宁夏空管分局航班信息处理系统为例,对航班信息处理系统结构以及软件架构进行分析,并对数据库数据进行对照检查。下发的长期计划数据中相关用户字段值错... 在航班信息处理系统(AIMS)各终端数据显示不一致的情况下寻找该问题的解决方法。以宁夏空管分局航班信息处理系统为例,对航班信息处理系统结构以及软件架构进行分析,并对数据库数据进行对照检查。下发的长期计划数据中相关用户字段值错误,导致数据权限受限,用户客户端无法显示航班数据。从故障现象到底层数据,从客户端数据显示到数据库数据分析,详细分析了此次案例产生的原因,为民航通信、导航、监视类设备维护维修提供了参考和排故思路。 展开更多
关键词 aimS 数据库 排故 提升服务 功能优化
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Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM
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作者 Lin Ma Liyong Wang +5 位作者 Shuang Zeng Yutong Zhao Chang Liu Heng Zhang Qiong Wu Hongbo Ren 《Energy Engineering》 EI 2024年第6期1473-1493,共21页
Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a s... Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons. 展开更多
关键词 short-term household load forecasting long short-term memory network attention mechanism hybrid deep learning framework
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Modeling injection-induced fault slip using long short-term memory networks
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作者 Utkarsh Mital Mengsu Hu +2 位作者 Yves Guglielmi James Brown Jonny Rutqvist 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第11期4354-4368,共15页
Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault.This can be due to subsurface(geo)engineering activities such as fluid injections an... Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault.This can be due to subsurface(geo)engineering activities such as fluid injections and geologic disposal of nuclear waste.Such activities are expected to rise in the future making it necessary to assess their short-and long-term safety.Here,a new machine learning(ML)approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed.The focus is on fault behavior near the injection borehole.To capture the temporal dependencies in the data,long short-term memory(LSTM)networks are utilized.To prevent error accumulation within the forecast window,four critical measures to train a robust LSTM model for predicting fault response are highlighted:(i)setting an appropriate value of LSTM lag,(ii)calibrating the LSTM cell dimension,(iii)learning rate reduction during weight optimization,and(iv)not adopting an independent injection cycle as a validation set.Several numerical experiments were conducted,which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection.The model also captured the decay in pressure and displacement during the injection shut-in period.Further,the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated,which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections. 展开更多
关键词 Machine learning Long short-term memory networks FAULT Fluid injection
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A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment
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作者 Haibo Li Yongbo Yu +1 位作者 Zhenbo Zhao Xiaokang Tang 《Computers, Materials & Continua》 SCIE EI 2024年第1期653-676,共24页
Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same g... Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method. 展开更多
关键词 Time series short-term prediction multi-granularity event ALIGNMENT event matching
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Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery
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作者 Dong Peng Zi-Wei Li +2 位作者 Fei Liu Xu-Rui Liu Chun-Yi Wang 《World Journal of Gastroenterology》 SCIE CAS 2024年第12期1714-1726,共13页
BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has... BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not. 展开更多
关键词 Colorectal cancer Red blood cell distribution width SURVIVAL short-term outcomes
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AIM2炎症复合体活化体系的体外构建及初步应用
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作者 许锦霞 吴龙建 +3 位作者 胡燕萍 孙敏捷 宋厚辉 杨杨 《中国预防兽医学报》 CAS CSCD 北大核心 2024年第2期178-184,共7页
AIM2炎症复合体参与自身免疫性疾病和机体抵御病原体的过程,研究其激活机制具有重要的意义。为构建AIM2炎症复合体的体外活化体系,本研究通过PCR方法从人单核细胞(THP-1细胞)中扩增AIM2、ASC、pro-Caspase-1、pro-IL-1β基因片段后,构... AIM2炎症复合体参与自身免疫性疾病和机体抵御病原体的过程,研究其激活机制具有重要的意义。为构建AIM2炎症复合体的体外活化体系,本研究通过PCR方法从人单核细胞(THP-1细胞)中扩增AIM2、ASC、pro-Caspase-1、pro-IL-1β基因片段后,构建重组质粒p3×Flag-AIM2、p3×Flag-ASC、p3×Flag-pro-Caspase-1和p3×Flag-pro-IL-1β,分别转染HEK293T细胞后采用western blot鉴定各蛋白的表达。结果显示,分别约在41.9 ku、34.1 ku、48.5 ku、24.6 ku处出现特异性条带,表明融合Flag标签的AIM2、ASC、Caspase-1和IL-1β蛋白在HEK293T细胞中获得了表达。除此之外,还可以在HEK293T细胞中检测到39 ku的内源性AIM2蛋白特异性条带,表明HEK293T细胞自身也表达内源性AIM2蛋白。将不同浓度比例的上述重组质粒转染或共转染HEK293T细胞,24 h后各组再转染poly(dA:dT),采用间接ELISA检测各组细胞中IL-1β的分泌水平。结果显示,空白对照组、p3×Flag-pro-IL-1β实验组和共转染p3×Flag-ASC、p3×Flag-pro-IL-1β实验组细胞上清中均未检测到IL-1β,共转染p3×Flag-ASC、p3×Flag-pro-Caspase-1、p3×Flag-pro-IL-1β和共转染p3×Flag-AIM2、p3×Flag-ASC、p3×Flag-pro-Caspase-1、p3×Flag-pro-IL-1β的实验组细胞上清中均能检测到高浓度的IL-1β,且共转染p3×Flag-AIM2的HEK293T细胞中IL-1β的分泌水平更高。此外,与对照组相比,poly(dA:dT)刺激后的各组HEK293T细胞中IL-1β的分泌水平极显著升高(P<0.001),表明AIM2炎症复合体的体外活化体系正确构建。将不同浓度的p3×Flag-AIM2与其它质粒共转染HEK293T细胞,并转染poly(dA:dT)作用,采用间接ELISA检测IL-1β的分泌水平,结果显示,无论是否转染poly(dA:dT),随着p3×Flag-AIM2的转染剂量的升高,IL-1β的分泌水平也显著或极显著升高(P<0.001、P<0.01、P<0.05、P<0.001),表明细胞中AIM2蛋白的表达量与AIM2炎症复合体的活性呈正相关。单核细胞增生性李斯特菌已被证实可以激活AIM2炎症复合体,利用该菌感染上述炎症复合体活化体系,6 h后采用LDH试剂盒检测各组细胞胞内细菌的存活情况。结果显示,细胞内单核细胞增生性李斯特菌的数量在感染2 h和6 h极显著低于不转染质粒的对照组(P<0.001、P<0.01),表明构建的AIM2炎症复合体活化体系发挥了抗细菌感染的作用。综上所述,本研究正确构建了AIM2炎症复合体活化体系,并初步通过该活化体系证实AIM2炎症复合体具有抗细菌感染的功能,为后续研究该活化体系的具体作用机制奠定了基础。 展开更多
关键词 质粒构建 aim2炎症复合体 IL-1Β
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Short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function
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作者 Li-Jun Yao Xiao-Ding Zhu +5 位作者 Liu-Min Zhou Li-Li Zhang Na-Na Liu Min Chen Jia-Ying Wang Shao-Jun Hu 《World Journal of Clinical Cases》 SCIE 2024年第18期3395-3402,共8页
BACKGROUND Hepatectomy is the first choice for treating liver cancer.However,inflammatory factors,released in response to pain stimulation,may suppress perioperative immune function and affect the prognosis of patient... BACKGROUND Hepatectomy is the first choice for treating liver cancer.However,inflammatory factors,released in response to pain stimulation,may suppress perioperative immune function and affect the prognosis of patients undergoing hepatectomies.AIM To determine the short-term efficacy of microwave ablation in the treatment of liver cancer and its effect on immune function.METHODS Clinical data from patients with liver cancer admitted to Suzhou Ninth People’s Hospital from January 2020 to December 2023 were retrospectively analyzed.Thirty-five patients underwent laparoscopic hepatectomy for liver cancer(liver cancer resection group)and 35 patients underwent medical image-guided microwave ablation(liver cancer ablation group).The short-term efficacy,complications,liver function,and immune function indices before and after treatment were compared between the two groups.RESULTS One month after treatment,19 patients experienced complete remission(CR),8 patients experienced partial remission(PR),6 patients experienced stable disease(SD),and 2 patients experienced disease progression(PD)in the liver cancer resection group.In the liver cancer ablation group,21 patients experienced CR,9 patients experienced PR,3 patients experienced SD,and 2 patients experienced PD.No significant differences in efficacy and complications were detected between the liver cancer ablation and liver cancer resection groups(P>0.05).After treatment,total bilirubin(41.24±7.35 vs 49.18±8.64μmol/L,P<0.001),alanine aminotransferase(30.85±6.23 vs 42.32±7.56 U/L,P<0.001),CD4+(43.95±5.72 vs 35.27±5.56,P<0.001),CD8+(20.38±3.91 vs 22.75±4.62,P<0.001),and CD4+/CD8+(2.16±0.39 vs 1.55±0.32,P<0.001)were significantly different between the liver cancer ablation and liver cancer resection groups.CONCLUSION The short-term efficacy and safety of microwave ablation and laparoscopic surgery for the treatment of liver cancer are similar,but liver function recovers quickly after microwave ablation,and microwave ablation may enhance immune function. 展开更多
关键词 Microwave ablation Liver cancer short-term efficacy Liver function Immunologic function
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Transformer-based correction scheme for short-term bus load prediction in holidays
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作者 Tang Ningkai Lu Jixiang +3 位作者 Chen Tianyu Shu Jiao Chang Li Chen Tao 《Journal of Southeast University(English Edition)》 EI CAS 2024年第3期304-312,共9页
To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduc... To tackle the problem of inaccurate short-term bus load prediction,especially during holidays,a Transformer-based scheme with tailored architectural enhancements is proposed.First,the input data are clustered to reduce complexity and capture inherent characteristics more effectively.Gated residual connections are then employed to selectively propagate salient features across layers,while an attention mechanism focuses on identifying prominent patterns in multivariate time-series data.Ultimately,a pre-trained structure is incorporated to reduce computational complexity.Experimental results based on extensive data show that the proposed scheme achieves improved prediction accuracy over comparative algorithms by at least 32.00%consistently across all buses evaluated,and the fitting effect of holiday load curves is outstanding.Meanwhile,the pre-trained structure drastically reduces the training time of the proposed algorithm by more than 65.75%.The proposed scheme can efficiently predict bus load results while enhancing robustness for holiday predictions,making it better adapted to real-world prediction scenarios. 展开更多
关键词 short-term bus load prediction Transformer network holiday load pre-training model load clustering
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An Enhanced Ensemble-Based Long Short-Term Memory Approach for Traffic Volume Prediction
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作者 Duy Quang Tran Huy Q.Tran Minh Van Nguyen 《Computers, Materials & Continua》 SCIE EI 2024年第3期3585-3602,共18页
With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning ... With the advancement of artificial intelligence,traffic forecasting is gaining more and more interest in optimizing route planning and enhancing service quality.Traffic volume is an influential parameter for planning and operating traffic structures.This study proposed an improved ensemble-based deep learning method to solve traffic volume prediction problems.A set of optimal hyperparameters is also applied for the suggested approach to improve the performance of the learning process.The fusion of these methodologies aims to harness ensemble empirical mode decomposition’s capacity to discern complex traffic patterns and long short-term memory’s proficiency in learning temporal relationships.Firstly,a dataset for automatic vehicle identification is obtained and utilized in the preprocessing stage of the ensemble empirical mode decomposition model.The second aspect involves predicting traffic volume using the long short-term memory algorithm.Next,the study employs a trial-and-error approach to select a set of optimal hyperparameters,including the lookback window,the number of neurons in the hidden layers,and the gradient descent optimization.Finally,the fusion of the obtained results leads to a final traffic volume prediction.The experimental results show that the proposed method outperforms other benchmarks regarding various evaluation measures,including mean absolute error,root mean squared error,mean absolute percentage error,and R-squared.The achieved R-squared value reaches an impressive 98%,while the other evaluation indices surpass the competing.These findings highlight the accuracy of traffic pattern prediction.Consequently,this offers promising prospects for enhancing transportation management systems and urban infrastructure planning. 展开更多
关键词 Ensemble empirical mode decomposition traffic volume prediction long short-term memory optimal hyperparameters deep learning
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Development and validation of a circulating tumor DNA-based optimization-prediction model for short-term postoperative recurrence of endometrial cancer
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作者 Yuan Liu Xiao-Ning Lu +3 位作者 Hui-Ming Guo Chan Bao Juan Zhang Yu-Ni Jin 《World Journal of Clinical Cases》 SCIE 2024年第18期3385-3394,共10页
BACKGROUND Endometrial cancer(EC)is a common gynecological malignancy that typically requires prompt surgical intervention;however,the advantage of surgical management is limited by the high postoperative recurrence r... BACKGROUND Endometrial cancer(EC)is a common gynecological malignancy that typically requires prompt surgical intervention;however,the advantage of surgical management is limited by the high postoperative recurrence rates and adverse outcomes.Previous studies have highlighted the prognostic potential of circulating tumor DNA(ctDNA)monitoring for minimal residual disease in patients with EC.AIM To develop and validate an optimized ctDNA-based model for predicting shortterm postoperative EC recurrence.METHODS We retrospectively analyzed 294 EC patients treated surgically from 2015-2019 to devise a short-term recurrence prediction model,which was validated on 143 EC patients operated between 2020 and 2021.Prognostic factors were identified using univariate Cox,Lasso,and multivariate Cox regressions.A nomogram was created to predict the 1,1.5,and 2-year recurrence-free survival(RFS).Model performance was assessed via receiver operating characteristic(ROC),calibration,and decision curve analyses(DCA),leading to a recurrence risk stratification system.RESULTS Based on the regression analysis and the nomogram created,patients with postoperative ctDNA-negativity,postoperative carcinoembryonic antigen 125(CA125)levels of<19 U/mL,and grade G1 tumors had improved RFS after surgery.The nomogram’s efficacy for recurrence prediction was confirmed through ROC analysis,calibration curves,and DCA methods,highlighting its high accuracy and clinical utility.Furthermore,using the nomogram,the patients were successfully classified into three risk subgroups.CONCLUSION The nomogram accurately predicted RFS after EC surgery at 1,1.5,and 2 years.This model will help clinicians personalize treatments,stratify risks,and enhance clinical outcomes for patients with EC. 展开更多
关键词 Circulating tumor DNA Endometrial cancer short-term recurrence Predictive model Prospective validation
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State-of-health estimation for fast-charging lithium-ion batteries based on a short charge curve using graph convolutional and long short-term memory networks
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作者 Yvxin He Zhongwei Deng +4 位作者 Jue Chen Weihan Li Jingjing Zhou Fei Xiang Xiaosong Hu 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2024年第11期1-11,共11页
A fast-charging policy is widely employed to alleviate the inconvenience caused by the extended charging time of electric vehicles. However, fast charging exacerbates battery degradation and shortens battery lifespan.... A fast-charging policy is widely employed to alleviate the inconvenience caused by the extended charging time of electric vehicles. However, fast charging exacerbates battery degradation and shortens battery lifespan. In addition, there is still a lack of tailored health estimations for fast-charging batteries;most existing methods are applicable at lower charging rates. This paper proposes a novel method for estimating the health of lithium-ion batteries, which is tailored for multi-stage constant current-constant voltage fast-charging policies. Initially, short charging segments are extracted by monitoring current switches,followed by deriving voltage sequences using interpolation techniques. Subsequently, a graph generation layer is used to transform the voltage sequence into graphical data. Furthermore, the integration of a graph convolution network with a long short-term memory network enables the extraction of information related to inter-node message transmission, capturing the key local and temporal features during the battery degradation process. Finally, this method is confirmed by utilizing aging data from 185 cells and 81 distinct fast-charging policies. The 4-minute charging duration achieves a balance between high accuracy in estimating battery state of health and low data requirements, with mean absolute errors and root mean square errors of 0.34% and 0.66%, respectively. 展开更多
关键词 Lithium-ion battery State of health estimation Feature extraction Graph convolutional network Long short-term memory network
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