As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS...As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.展开更多
In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer...In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer phenomenon is involved.Fourier’s law of heat conduction has been used as the foundation for predicting the heat transfer behavior in a variety of real-world contexts.This model’s production of a parabolic energy expression,which means that an initial disturbance would immediately affect the system under investigation,is one of its main drawbacks.Therefore,numerous researchers worked on such problem to resolve this issue.At last,this problem was resolved by Cattaneo by adding relaxation time for heat flux in Fourier’s law,which was defined as the time required to establish steady heat conduction once a temperature gradient is imposed.Christov offered a material invariant version of Cattaneo’s model by taking into account the upper-connected derivative of the Oldroyd model.Nowadays,both models are combinedly known as the Cattaneo-Christov(CC)model.In this attempt,the mixed convective MHD Falkner-Skan Sutterby nanofluid flow is addressed towards a wedge surface in the presence of the variable external magnetic field.The CC model is incorporated instead of Fourier’s law for the examination of heat transfer features in the energy expression.A two-phase nanofluid model is utilized for the implementation of nano-concept.The nonlinear system of equations is tackled through the bvp4c technique in the MATLAB software 2016.The influence of pertinent flow parameters is discussed and displayed through different sketches.Major and important results are summarized in the conclusion section.Furthermore,in both cases of wall-through flow(i.e.,suction and injection effects),the porosity parameters increase the flow speed,and decrease the heat transport and the influence of drag forces.展开更多
1 M-P神经元模型的工作原理和几何意义
1943年,MoCulloch和Pitts[1]根据神经元传递规律,第一次提出了神经元的数学模型.M-P神经元模型一直沿用至今,它对神经网络的发展起到了奠基性的作用.每个神经元的状态由M-P方程决定:S=f(∑W X -θ)...1 M-P神经元模型的工作原理和几何意义
1943年,MoCulloch和Pitts[1]根据神经元传递规律,第一次提出了神经元的数学模型.M-P神经元模型一直沿用至今,它对神经网络的发展起到了奠基性的作用.每个神经元的状态由M-P方程决定:S=f(∑W X -θ),θ为阈值,f为激励函数,一般取符号函数.令:它代表了n维空间中,以X为坐标变量,以W为坐标系数,θ为常数项的一个超平面.当样本点X落入超平面的正半区,即I(X)>0时,有f(I)＝1;当样本点X落入超平面的负半区,即I(X)<0时,有f(I)＝0.从分类的角度看,一个神经元按输入将样本划分成为两类(0和1).现在广泛使用的BP模型采用Sigmoid函数作为激励函数,但是它没有改变神经元分类的本质.神经网络实际上就是多个神经元组织起来的一种网状结构.展开更多
考虑碳交易价格、燃料价格、投资成本及政府补贴等不确定性因素,基于实物期权理论构建了燃煤电站碳捕获与储存(carbon capture and storage,CCS)投资决策的四叉树模型,通过算例分析了模型的求解过程,证实了实物期权方法比传统的净现值(N...考虑碳交易价格、燃料价格、投资成本及政府补贴等不确定性因素,基于实物期权理论构建了燃煤电站碳捕获与储存(carbon capture and storage,CCS)投资决策的四叉树模型,通过算例分析了模型的求解过程,证实了实物期权方法比传统的净现值(NPV)方法能更准确地评估CCS的投资价值;进一步研究了政策补贴对CCS投资决策的影响,并计算出不同政策补贴系数下碳交易价格的投资临界值。结果表明,政策补贴越高则碳价格临界值越低,当政府提供全额补贴和不提供补贴时,碳交易临界价格分别为103.56元/t和217.95元/t。这意味着在当前市场环境下,电站CCS投资会导致亏损。上述结论对燃煤电站的CCS投资决策提供了理论依据。展开更多
利用生物信息学方法筛选与宫颈癌发生、发展和预后相关的血管生成相关基因(angiogenesis related gene,ARG),并进行相关预后风险模型的构建与验证。首先,从TCGA数据库中检索宫颈癌患者的表达谱和临床特征,并提取差异表达的ARG;其次,采用...利用生物信息学方法筛选与宫颈癌发生、发展和预后相关的血管生成相关基因(angiogenesis related gene,ARG),并进行相关预后风险模型的构建与验证。首先,从TCGA数据库中检索宫颈癌患者的表达谱和临床特征,并提取差异表达的ARG;其次,采用Lasso Cox回归筛选预后ARG,构建相关预后模型;再次,使用GSE52903和GSE44001数据集进行外部验证;最后,利用基因集富集分析(gene set enrichment analysis,GSEA)探讨宫颈癌预后机制。筛选结果显示,共获得15个预后ARG,分别为EFNA1、ITGA5、EPHB4、NRP1、CDH5、PLAU、BMP6、DLL4、JUN、CA9、MMP1、BAIAP2L1、SERPINF1、F2RL1和FGFR2。GSE52903和GSE44001数据集的Kaplan-Meier生存曲线显示,高风险组的总生存期(overall survival,OS)(P=0.005)和无病生存期(disease-free survival,DFS)(P<0.001)显著低于低风险组。受试者操作特征(receiver operating characteristic,ROC)曲线分析结果显示,GSE52903验证集在1年、3年和5年的曲线下面积(area under the curve,AUC)值分别为0.84、0.77和0.73,C-指数为0.72;GSE44001验证集在1年、3年和5年的AUC值分别为0.71、0.72和0.70,C-指数为0.70,说明该模型对患者预后具有很强的预测效能。GSEA分析富集的通路主要涉及DNA复制、细胞外基质(extracellular matrix,ECM)受体相互作用、补体和凝血级联等,这些过程与宫颈癌发生、发展紧密相关。以上结果表明,这15个关键ARG可能是宫颈癌预后潜在的生物标志物。展开更多
利用通信系统演算CCS(Calculus of Communicating Systems),对用来解决进程间通信问题的信号量给出了形式化建模和验证的方法,并利用该方法对以信号量机制解决生产者—消费者问题和哲学家进餐问题进行建模、逻辑说明和验证。该方法具有...利用通信系统演算CCS(Calculus of Communicating Systems),对用来解决进程间通信问题的信号量给出了形式化建模和验证的方法,并利用该方法对以信号量机制解决生产者—消费者问题和哲学家进餐问题进行建模、逻辑说明和验证。该方法具有一定通用性,并可将其推广到其他通过信号量机制解决进程通信的问题当中。展开更多
文摘As the demand for more efficient and adaptable power distribution systems intensifies, especially in rural areas, innovative solutions like the Capacitor-Coupled Substation with a Controllable Network Transformer (CCS-CNT) are becoming increasingly critical. Traditional power distribution networks, often limited by unidirectional flow capabilities and inflexibility, struggle to meet the complex demands of modern energy systems. The CCS-CNT system offers a transformative approach by enabling bidirectional power flow between high-voltage transmission lines and local distribution networks, a feature that is essential for integrating renewable energy sources and ensuring reliable electrification in underserved regions. This paper presents a detailed mathematical representation of power flow within the CCS-CNT system, emphasizing the control of both active and reactive power through the adjustment of voltage levels and phase angles. A control algorithm is developed to dynamically manage power flow, ensuring optimal performance by minimizing losses and maintaining voltage stability across the network. The proposed CCS-CNT system demonstrates significant potential in enhancing the efficiency and reliability of power distribution, making it particularly suited for rural electrification and other applications where traditional methods fall short. The findings underscore the system's capability to adapt to varying operational conditions, offering a robust solution for modern power distribution challenges.
基金Deanship of Scientific Research at King Khalid University for funding this work through Large Group Research Project(No.RGP2/19/44)。
文摘In a wide variety of mechanical and industrial applications,e.g.,space cooling,nuclear reactor cooling,medicinal utilizations(magnetic drug targeting),energy generation,and heat conduction in tissues,the heat transfer phenomenon is involved.Fourier’s law of heat conduction has been used as the foundation for predicting the heat transfer behavior in a variety of real-world contexts.This model’s production of a parabolic energy expression,which means that an initial disturbance would immediately affect the system under investigation,is one of its main drawbacks.Therefore,numerous researchers worked on such problem to resolve this issue.At last,this problem was resolved by Cattaneo by adding relaxation time for heat flux in Fourier’s law,which was defined as the time required to establish steady heat conduction once a temperature gradient is imposed.Christov offered a material invariant version of Cattaneo’s model by taking into account the upper-connected derivative of the Oldroyd model.Nowadays,both models are combinedly known as the Cattaneo-Christov(CC)model.In this attempt,the mixed convective MHD Falkner-Skan Sutterby nanofluid flow is addressed towards a wedge surface in the presence of the variable external magnetic field.The CC model is incorporated instead of Fourier’s law for the examination of heat transfer features in the energy expression.A two-phase nanofluid model is utilized for the implementation of nano-concept.The nonlinear system of equations is tackled through the bvp4c technique in the MATLAB software 2016.The influence of pertinent flow parameters is discussed and displayed through different sketches.Major and important results are summarized in the conclusion section.Furthermore,in both cases of wall-through flow(i.e.,suction and injection effects),the porosity parameters increase the flow speed,and decrease the heat transport and the influence of drag forces.
文摘1 M-P神经元模型的工作原理和几何意义
1943年,MoCulloch和Pitts[1]根据神经元传递规律,第一次提出了神经元的数学模型.M-P神经元模型一直沿用至今,它对神经网络的发展起到了奠基性的作用.每个神经元的状态由M-P方程决定:S=f(∑W X -θ),θ为阈值,f为激励函数,一般取符号函数.令:它代表了n维空间中,以X为坐标变量,以W为坐标系数,θ为常数项的一个超平面.当样本点X落入超平面的正半区,即I(X)>0时,有f(I)＝1;当样本点X落入超平面的负半区,即I(X)<0时,有f(I)＝0.从分类的角度看,一个神经元按输入将样本划分成为两类(0和1).现在广泛使用的BP模型采用Sigmoid函数作为激励函数,但是它没有改变神经元分类的本质.神经网络实际上就是多个神经元组织起来的一种网状结构.
文摘考虑碳交易价格、燃料价格、投资成本及政府补贴等不确定性因素,基于实物期权理论构建了燃煤电站碳捕获与储存(carbon capture and storage,CCS)投资决策的四叉树模型,通过算例分析了模型的求解过程,证实了实物期权方法比传统的净现值(NPV)方法能更准确地评估CCS的投资价值;进一步研究了政策补贴对CCS投资决策的影响,并计算出不同政策补贴系数下碳交易价格的投资临界值。结果表明,政策补贴越高则碳价格临界值越低,当政府提供全额补贴和不提供补贴时,碳交易临界价格分别为103.56元/t和217.95元/t。这意味着在当前市场环境下,电站CCS投资会导致亏损。上述结论对燃煤电站的CCS投资决策提供了理论依据。
文摘利用生物信息学方法筛选与宫颈癌发生、发展和预后相关的血管生成相关基因(angiogenesis related gene,ARG),并进行相关预后风险模型的构建与验证。首先,从TCGA数据库中检索宫颈癌患者的表达谱和临床特征,并提取差异表达的ARG;其次,采用Lasso Cox回归筛选预后ARG,构建相关预后模型;再次,使用GSE52903和GSE44001数据集进行外部验证;最后,利用基因集富集分析(gene set enrichment analysis,GSEA)探讨宫颈癌预后机制。筛选结果显示,共获得15个预后ARG,分别为EFNA1、ITGA5、EPHB4、NRP1、CDH5、PLAU、BMP6、DLL4、JUN、CA9、MMP1、BAIAP2L1、SERPINF1、F2RL1和FGFR2。GSE52903和GSE44001数据集的Kaplan-Meier生存曲线显示,高风险组的总生存期(overall survival,OS)(P=0.005)和无病生存期(disease-free survival,DFS)(P<0.001)显著低于低风险组。受试者操作特征(receiver operating characteristic,ROC)曲线分析结果显示,GSE52903验证集在1年、3年和5年的曲线下面积(area under the curve,AUC)值分别为0.84、0.77和0.73,C-指数为0.72;GSE44001验证集在1年、3年和5年的AUC值分别为0.71、0.72和0.70,C-指数为0.70,说明该模型对患者预后具有很强的预测效能。GSEA分析富集的通路主要涉及DNA复制、细胞外基质(extracellular matrix,ECM)受体相互作用、补体和凝血级联等,这些过程与宫颈癌发生、发展紧密相关。以上结果表明,这15个关键ARG可能是宫颈癌预后潜在的生物标志物。
文摘利用通信系统演算CCS(Calculus of Communicating Systems),对用来解决进程间通信问题的信号量给出了形式化建模和验证的方法,并利用该方法对以信号量机制解决生产者—消费者问题和哲学家进餐问题进行建模、逻辑说明和验证。该方法具有一定通用性,并可将其推广到其他通过信号量机制解决进程通信的问题当中。
