The aftermath of the war had devastating consequences on people’s lives and society as a whole.In addition to the significant impact of the Great Depression on social production and living standards,it resulted in ps...The aftermath of the war had devastating consequences on people’s lives and society as a whole.In addition to the significant impact of the Great Depression on social production and living standards,it resulted in psychological trauma,unemployment,poverty,and social conflicts.As a prominent English poet that emerged after World War II,Geoffrey Hill depicted the gruesome realities of war through his early works.This article applies Cathy Caruth’s trauma theory to analyze Hill’s poem“Funeral Music.”The fragmented images and repetitive traumatic scenes restore the harsh realities of war.Furthermore,this article explores Joshua Pederson’s critical development of Caruth’s theoretical framework,providing an alternate perspective for textual analysis.展开更多
针对传统超声波测风装置测风精度不高、抗噪声能力弱,提出了一种改进多重信号分类(multiple signal classification,MUSIC)算法的超声波测风方法。采用一种弧形6阵元超声波传感器阵列的测风结构,推导其阵列流型;在此基础上,添加小波阈...针对传统超声波测风装置测风精度不高、抗噪声能力弱,提出了一种改进多重信号分类(multiple signal classification,MUSIC)算法的超声波测风方法。采用一种弧形6阵元超声波传感器阵列的测风结构,推导其阵列流型;在此基础上,添加小波阈值降噪算法提高信号信噪比,降低噪声信号协方差矩阵的秩;再使用PHAT加权广义互相关时延估计算法以提高时延估计的准确性,同时根据时延关系对传统MUSIC算法矢量矩阵进行改进;最后通过MUSIC算法实现对风速风向的测量。理论分析与仿真结果表明:改进后的MUSIC算法具有较好的抗噪性能和较高的风参数测量精度,测量风速绝对误差达到0.15 m/s,风向绝对误差达到2°,可以应用于对风参数要求较高的场景。展开更多
超声波检测方法在电力设备绝缘状态检测定位中应用广泛。针对局部放电超声测向MUSIC算法存在的采样率要求高、计算复杂度大等不足,提出基于定向超声阵列信号强度信息的定向多重信号分类(directional multiple signal classification,Dir...超声波检测方法在电力设备绝缘状态检测定位中应用广泛。针对局部放电超声测向MUSIC算法存在的采样率要求高、计算复杂度大等不足,提出基于定向超声阵列信号强度信息的定向多重信号分类(directional multiple signal classification,Dir-MUSIC)算法。在阐述该算法理论模型和应用条件基础上,针对均匀圆盘超声阵列,仿真研究了不同增益方向图主瓣宽度、不同信噪比条件下Dir-MUSIC算法的测向精度。仿真结果表明8阵元阵列在-5 dB信噪比、方向图主瓣宽度为90°~120°时测向精度最高,均方根误差小于2°。最后基于研制的微型机电系统麦克风(microelectro-mechanical system,MEMS)定向超声阵列进行了测向试验,结果表明8阵元圆盘超声阵列测向均方根误差最小为2.76°,测向标准差最小为2.72°,验证了Dir-MUSIC算法的有效性与准确性。展开更多
局部放电是衡量电力设备绝缘状态的重要指标,局放检测需要解决局放源定位问题。多重信号分类(multiple signal classification,MUSIC)采用全向天线作为接收阵列,可实现多源信号的超分辨率空间谱估计,但要求高信号采样率,且在低信噪比情...局部放电是衡量电力设备绝缘状态的重要指标,局放检测需要解决局放源定位问题。多重信号分类(multiple signal classification,MUSIC)采用全向天线作为接收阵列,可实现多源信号的超分辨率空间谱估计,但要求高信号采样率,且在低信噪比情况下抗干扰能力不足。为此,提出基于弧形阵列的Dir(directional)-MUSIC算法,采用定向天线接收信号的强度信息,实现低信噪比下的局放源波达方向估计。设计了接收局放信号的Vivaldi天线阵列,并在不同信噪比下对算法的有效性进行仿真验证。结果表明:在低信噪比-10 dB来波方向5°下角度误差为0.14°,优于MUSIC算法;阵列在信噪比10 dB,测向范围[-80°,80°]内定位均方根误差小于1.5°。证明了基于弧形阵列的Dir-MUSIC算法有效提高了局放定位精度,且对噪声具有良好的鲁棒性,具有用于局放检测的潜力。展开更多
BACKGROUND Musical hallucinations(MH)involve the false perception of music in the absence of external stimuli which links with different etiologies.The pathomechanisms of MH encompass various conditions.The etiologica...BACKGROUND Musical hallucinations(MH)involve the false perception of music in the absence of external stimuli which links with different etiologies.The pathomechanisms of MH encompass various conditions.The etiological classification of MH is of particular importance and offers valuable insights to understand MH,and further to develop the effective treatment of MH.Over the recent decades,more MH cases have been reported,revealing newly identified medical and psychiatric causes of MH.Functional imaging studies reveal that MH activates a wide array of brain regions.An up-to-date analysis on MH,especially on MH comorbid psychiatric conditions is warranted.AIM To propose a new classification of MH;to study the age and gender differences of MH in mental disorders;and neuropathology of MH.METHODS Literatures searches were conducted using keywords such as“music hallucination,”“music hallucination and mental illness,”“music hallucination and gender difference,”and“music hallucination and psychiatric disease”in the databases of PubMed,Google Scholar,and Web of Science.MH cases were collected and categorized based on their etiologies.The t-test and ANOVA were employed(P<0.05)to compare the age differences of MH different etiological groups.Function neuroimaging studies of neural networks regulating MH and their possible molecular mechanisms were discussed.RESULTS Among the 357 yielded publications,294 MH cases were collected.The average age of MH cases was 67.9 years,with a predominance of females(66.8%females vs 33.2%males).MH was classified into eight groups based on their etiological mechanisms.Statistical analysis of MH cases indicates varying associations with psychiatric diagnoses.CONCLUSION We carried out a more comprehensive review of MH studies.For the first time according to our knowledge,we demonstrated the psychiatric conditions linked and/or associated with MH from statistical,biological and molecular point of view.展开更多
文摘The aftermath of the war had devastating consequences on people’s lives and society as a whole.In addition to the significant impact of the Great Depression on social production and living standards,it resulted in psychological trauma,unemployment,poverty,and social conflicts.As a prominent English poet that emerged after World War II,Geoffrey Hill depicted the gruesome realities of war through his early works.This article applies Cathy Caruth’s trauma theory to analyze Hill’s poem“Funeral Music.”The fragmented images and repetitive traumatic scenes restore the harsh realities of war.Furthermore,this article explores Joshua Pederson’s critical development of Caruth’s theoretical framework,providing an alternate perspective for textual analysis.
文摘针对传统超声波测风装置测风精度不高、抗噪声能力弱,提出了一种改进多重信号分类(multiple signal classification,MUSIC)算法的超声波测风方法。采用一种弧形6阵元超声波传感器阵列的测风结构,推导其阵列流型;在此基础上,添加小波阈值降噪算法提高信号信噪比,降低噪声信号协方差矩阵的秩;再使用PHAT加权广义互相关时延估计算法以提高时延估计的准确性,同时根据时延关系对传统MUSIC算法矢量矩阵进行改进;最后通过MUSIC算法实现对风速风向的测量。理论分析与仿真结果表明:改进后的MUSIC算法具有较好的抗噪性能和较高的风参数测量精度,测量风速绝对误差达到0.15 m/s,风向绝对误差达到2°,可以应用于对风参数要求较高的场景。
文摘局部放电是衡量电力设备绝缘状态的重要指标,局放检测需要解决局放源定位问题。多重信号分类(multiple signal classification,MUSIC)采用全向天线作为接收阵列,可实现多源信号的超分辨率空间谱估计,但要求高信号采样率,且在低信噪比情况下抗干扰能力不足。为此,提出基于弧形阵列的Dir(directional)-MUSIC算法,采用定向天线接收信号的强度信息,实现低信噪比下的局放源波达方向估计。设计了接收局放信号的Vivaldi天线阵列,并在不同信噪比下对算法的有效性进行仿真验证。结果表明:在低信噪比-10 dB来波方向5°下角度误差为0.14°,优于MUSIC算法;阵列在信噪比10 dB,测向范围[-80°,80°]内定位均方根误差小于1.5°。证明了基于弧形阵列的Dir-MUSIC算法有效提高了局放定位精度,且对噪声具有良好的鲁棒性,具有用于局放检测的潜力。
文摘BACKGROUND Musical hallucinations(MH)involve the false perception of music in the absence of external stimuli which links with different etiologies.The pathomechanisms of MH encompass various conditions.The etiological classification of MH is of particular importance and offers valuable insights to understand MH,and further to develop the effective treatment of MH.Over the recent decades,more MH cases have been reported,revealing newly identified medical and psychiatric causes of MH.Functional imaging studies reveal that MH activates a wide array of brain regions.An up-to-date analysis on MH,especially on MH comorbid psychiatric conditions is warranted.AIM To propose a new classification of MH;to study the age and gender differences of MH in mental disorders;and neuropathology of MH.METHODS Literatures searches were conducted using keywords such as“music hallucination,”“music hallucination and mental illness,”“music hallucination and gender difference,”and“music hallucination and psychiatric disease”in the databases of PubMed,Google Scholar,and Web of Science.MH cases were collected and categorized based on their etiologies.The t-test and ANOVA were employed(P<0.05)to compare the age differences of MH different etiological groups.Function neuroimaging studies of neural networks regulating MH and their possible molecular mechanisms were discussed.RESULTS Among the 357 yielded publications,294 MH cases were collected.The average age of MH cases was 67.9 years,with a predominance of females(66.8%females vs 33.2%males).MH was classified into eight groups based on their etiological mechanisms.Statistical analysis of MH cases indicates varying associations with psychiatric diagnoses.CONCLUSION We carried out a more comprehensive review of MH studies.For the first time according to our knowledge,we demonstrated the psychiatric conditions linked and/or associated with MH from statistical,biological and molecular point of view.
