A generalized form of the error function, Gp(x)=pΓ(1/p)∫0xe−tpdt, which is directly associated with the gamma function, is evaluated for arbitrary real values of p>1and 0x≤+∞by employing a fast-converging power...A generalized form of the error function, Gp(x)=pΓ(1/p)∫0xe−tpdt, which is directly associated with the gamma function, is evaluated for arbitrary real values of p>1and 0x≤+∞by employing a fast-converging power series expansion developed in resolving the so-called Grandi’s paradox. Comparisons with accurate tabulated values for well-known cases such as the error function are presented using the expansions truncated at various orders.展开更多
Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could n...Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.展开更多
With recent advances in biotechnology, genome-wide association study （GWAS） has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistica...With recent advances in biotechnology, genome-wide association study （GWAS） has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression （LR） based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk of inflating type I error and reducing power. Dimension reduction-based techniques, such as principal component-based logistic regression （PC-LR）, partial least squares-based logistic regression （PLS-LR）, have recently gained much attention in the analysis of high dimensional genomic data. However, the perfor- mance of these methods is still not clear, especially in GWAS. We conducted simulations and real data application to compare the type I error and power of PC-LR, PLS-LR and LR applicable to GWAS within a defined single nucleotide polymorphism （SNP） set region. We found that PC-LR and PLS can reasonably control type I error under null hypothesis. On contrast, LR, which is corrected by Bonferroni method, was more conserved in all simulation settings. In particular, we found that PC-LR and PLS-LR had comparable power and they both outperformed LR, especially when the causal SNP was in high linkage disequilibrium with genotyped ones and with a small effective size in simulation. Based on SNP set analysis, we applied all three methods to analyze non-small cell lung cancer GWAS data.展开更多
Purpose： Long-term training specificity is thought to alter performance in tests evaluating strength and power production capability. The aim of the present study was to provide additional information to the limited ...Purpose： Long-term training specificity is thought to alter performance in tests evaluating strength and power production capability. The aim of the present study was to provide additional information to the limited existing knowledge concerning the possible differences of the force/time profile of squat jumping among different groups of young female athletes. Methods： One hundred and seventy-three adult women （20.1 ± 2.8 years, 1.71 ± 0.09 m, 65.6 ± 10.3 kg, mean± SD for age, height, and mass, respectively） engaged in track and field （TF）, volleyball （VO）, handball （HA）, basketball （BA）, and physical education students （PE） executed maximal squat jumps （SQJ） on a force plate. Pearson＇s correlation was used to identify the relationship between SQJ performance, the anthropometric characteristics and the biomechanical parameters. Differences concerning the biomechanical parameters among groups were investigated with analysis of variance, while the force- （FPD） or time- （TPD） dependency of SQJ execution was examined using principal components analysis （PCA）. Results： SQJ was unrelated to body height but significantly correlated with body mass （r = -0.26, p = 0.001）. TF jumped higher and produced larger peak body power output compared to all the other groups （p 〈 0.05）. All athletes were superior to PE since they performed the SQJ with a longer （p 〈 0.05） vertical body center of mass trajectory during the propulsion phase. PCA results revealed that TF significantly differentiated than the other groups by relying on FPD. Conclusion： Various different profiles of FPD and TPD were detected due to different sporting background in young female athletes. Since TF superiority in SQJ was relied on the larger power production and a greater FPD, female indoor team sport athletes are suggested to execute jumping exercises adopting the jumping strategies utilized by TE展开更多
串联同步开关电感(Series Synchronous Switch Harvesting on Inductor,S-SSHI)电路输出功率高整流电压范围窄,而同步电荷提取(Synchronous Electric Charge Extraction,SECE)电路则输出功率低整流电压范围宽。提出了一种基于S-SSHI和S...串联同步开关电感(Series Synchronous Switch Harvesting on Inductor,S-SSHI)电路输出功率高整流电压范围窄,而同步电荷提取(Synchronous Electric Charge Extraction,SECE)电路则输出功率低整流电压范围宽。提出了一种基于S-SSHI和SECE混合的压电阵列能量俘获接口电路,以实现整流器峰值输出功率和最佳整流电压范围之间的平衡。所提出的电路去除了整流桥结构,而采用简单的无源峰值检测器设计,且可以在任意相位差(0~2π)下从多个压电换能器中提取能量。仿真和实验结果表明,所提出的电路具有较高的输出功率和较宽的整流电压范围,与多输入全桥整流器相比,最大输出功率提升了3.04倍。展开更多
为提高非平稳响应信号瞬时频率的识别效果,提出基于滑动窗宽优化的局部最大同步挤压广义S变换(local maximum synchrosqueezing generalized S-transform,LMSSGST)。该方法首先对非平稳响应信号进行广义S变换获得相应的时频系数;其次,...为提高非平稳响应信号瞬时频率的识别效果,提出基于滑动窗宽优化的局部最大同步挤压广义S变换(local maximum synchrosqueezing generalized S-transform,LMSSGST)。该方法首先对非平稳响应信号进行广义S变换获得相应的时频系数;其次,利用该响应信号的功率谱密度特征曲线确定局部最大同步挤压算子中滑动窗的宽度;再次,通过局部最大同步挤压算子进行时频重排;最后,采用模极大值改进算法提取瞬时频率曲线。通过两个数值算例、一个滑动窗宽参数分析和一个时变拉索试验验证了所提方法的有效性,研究结果表明:利用功率谱密度特征曲线能够有效确定滑动窗的窗宽和模极大值算法的提取范围。相比局部最大同步挤压变换算法,基于滑动窗宽优化的LMSSGST具有更佳的瞬时频率识别效果。展开更多
电源网络S参数与芯片电源模型(Chip Power Module,CPM)级联可实现电源时域噪声仿真,完成电源完整性设计签核。当下部分仿真工具在AC阻抗优化过程中导出的S参数存在低频段无法覆盖的问题,影响时域纹波仿真精度,如果重新对S参数进行提取,...电源网络S参数与芯片电源模型(Chip Power Module,CPM)级联可实现电源时域噪声仿真,完成电源完整性设计签核。当下部分仿真工具在AC阻抗优化过程中导出的S参数存在低频段无法覆盖的问题,影响时域纹波仿真精度,如果重新对S参数进行提取,又会增加仿真时间降低仿真效率。针对AC阻抗优化过程中导出的S参数无法覆盖低频段的问题,提出了一种电源网络S参数低频段拓展方法,结合电压调节模块(Voltage Regulator Module,VRM)的R-L模型,推导出低频段的S参数可以借用抽取的S参数中最低频点处的S参数实现低频段S参数的拓展。仿真和实验结果表明,通过对低频段S参数进行拓展,电源时域纹波噪声仿真的精度提升31%。同时,低频段的S参数直接借用已抽取的S参数中低频点的数值无须重复提取,在8 GB内存的配置下,仿真时间节约14%左右,提高了仿真效率。展开更多
文摘A generalized form of the error function, Gp(x)=pΓ(1/p)∫0xe−tpdt, which is directly associated with the gamma function, is evaluated for arbitrary real values of p>1and 0x≤+∞by employing a fast-converging power series expansion developed in resolving the so-called Grandi’s paradox. Comparisons with accurate tabulated values for well-known cases such as the error function are presented using the expansions truncated at various orders.
基金Supported by the Science and Technology Research Project Fund of Provincial Department of Education(12531004)Project of Heilongjiang Leading Talent Echelon Talented(2012)
文摘Power load forecasting accuracy related to the development of the power system. There were so many factors influencing the power load, but their effects were not the same and what factors played a leading role could not be determined empirically. Based on the analysis of the principal component, the paper forecasted the demands of power load with the method of the multivariate linear regression model prediction. Took the rural power grid load for example, the paper analyzed the impacts of different factors on power load, selected the forecast methods which were appropriate for using in this area, forecasted its 2014-2018 electricity load, and provided a reliable basis for grid planning.
基金founded by the National Natural Science Foundation of China(81202283,81473070,81373102 and81202267)Key Grant of Natural Science Foundation of the Jiangsu Higher Education Institutions of China(10KJA330034 and11KJA330001)+1 种基金the Research Fund for the Doctoral Program of Higher Education of China(20113234110002)the Priority Academic Program for the Development of Jiangsu Higher Education Institutions(Public Health and Preventive Medicine)
文摘With recent advances in biotechnology, genome-wide association study （GWAS） has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression （LR） based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk of inflating type I error and reducing power. Dimension reduction-based techniques, such as principal component-based logistic regression （PC-LR）, partial least squares-based logistic regression （PLS-LR）, have recently gained much attention in the analysis of high dimensional genomic data. However, the perfor- mance of these methods is still not clear, especially in GWAS. We conducted simulations and real data application to compare the type I error and power of PC-LR, PLS-LR and LR applicable to GWAS within a defined single nucleotide polymorphism （SNP） set region. We found that PC-LR and PLS can reasonably control type I error under null hypothesis. On contrast, LR, which is corrected by Bonferroni method, was more conserved in all simulation settings. In particular, we found that PC-LR and PLS-LR had comparable power and they both outperformed LR, especially when the causal SNP was in high linkage disequilibrium with genotyped ones and with a small effective size in simulation. Based on SNP set analysis, we applied all three methods to analyze non-small cell lung cancer GWAS data.
文摘Purpose： Long-term training specificity is thought to alter performance in tests evaluating strength and power production capability. The aim of the present study was to provide additional information to the limited existing knowledge concerning the possible differences of the force/time profile of squat jumping among different groups of young female athletes. Methods： One hundred and seventy-three adult women （20.1 ± 2.8 years, 1.71 ± 0.09 m, 65.6 ± 10.3 kg, mean± SD for age, height, and mass, respectively） engaged in track and field （TF）, volleyball （VO）, handball （HA）, basketball （BA）, and physical education students （PE） executed maximal squat jumps （SQJ） on a force plate. Pearson＇s correlation was used to identify the relationship between SQJ performance, the anthropometric characteristics and the biomechanical parameters. Differences concerning the biomechanical parameters among groups were investigated with analysis of variance, while the force- （FPD） or time- （TPD） dependency of SQJ execution was examined using principal components analysis （PCA）. Results： SQJ was unrelated to body height but significantly correlated with body mass （r = -0.26, p = 0.001）. TF jumped higher and produced larger peak body power output compared to all the other groups （p 〈 0.05）. All athletes were superior to PE since they performed the SQJ with a longer （p 〈 0.05） vertical body center of mass trajectory during the propulsion phase. PCA results revealed that TF significantly differentiated than the other groups by relying on FPD. Conclusion： Various different profiles of FPD and TPD were detected due to different sporting background in young female athletes. Since TF superiority in SQJ was relied on the larger power production and a greater FPD, female indoor team sport athletes are suggested to execute jumping exercises adopting the jumping strategies utilized by TE
文摘串联同步开关电感(Series Synchronous Switch Harvesting on Inductor,S-SSHI)电路输出功率高整流电压范围窄,而同步电荷提取(Synchronous Electric Charge Extraction,SECE)电路则输出功率低整流电压范围宽。提出了一种基于S-SSHI和SECE混合的压电阵列能量俘获接口电路,以实现整流器峰值输出功率和最佳整流电压范围之间的平衡。所提出的电路去除了整流桥结构,而采用简单的无源峰值检测器设计,且可以在任意相位差(0~2π)下从多个压电换能器中提取能量。仿真和实验结果表明,所提出的电路具有较高的输出功率和较宽的整流电压范围,与多输入全桥整流器相比,最大输出功率提升了3.04倍。
文摘为提高非平稳响应信号瞬时频率的识别效果,提出基于滑动窗宽优化的局部最大同步挤压广义S变换(local maximum synchrosqueezing generalized S-transform,LMSSGST)。该方法首先对非平稳响应信号进行广义S变换获得相应的时频系数;其次,利用该响应信号的功率谱密度特征曲线确定局部最大同步挤压算子中滑动窗的宽度;再次,通过局部最大同步挤压算子进行时频重排;最后,采用模极大值改进算法提取瞬时频率曲线。通过两个数值算例、一个滑动窗宽参数分析和一个时变拉索试验验证了所提方法的有效性,研究结果表明:利用功率谱密度特征曲线能够有效确定滑动窗的窗宽和模极大值算法的提取范围。相比局部最大同步挤压变换算法,基于滑动窗宽优化的LMSSGST具有更佳的瞬时频率识别效果。
