目的:总结MAB21L2基因的变异和临床特点,并与高度同源的MAB21L1基因进行比较。方法:对中山眼科中心临床基因数据库中MAB21L2基因变异患者进行基因型和表型分析,回顾性分析既往文献报道的MAB21L2基因和高度同源基因MAB21L1变异的表型-基...目的:总结MAB21L2基因的变异和临床特点,并与高度同源的MAB21L1基因进行比较。方法:对中山眼科中心临床基因数据库中MAB21L2基因变异患者进行基因型和表型分析,回顾性分析既往文献报道的MAB21L2基因和高度同源基因MAB21L1变异的表型-基因型的关系。结果:在2个小眼畸形家系中发现2个MAB21L2基因杂合变异:先证者1携带已知变异c.151C>G/p.(Arg51Gly),患者双眼小眼畸形伴虹膜脉络膜缺损,伴骨关节屈曲。母亲携带相同杂合变异但表型正常;先证者2携带未报道的变异c.1042G>T/p.(Glu348*),左眼小眼畸形,右眼正常且无全身异常。结合文献回顾发现,在显性遗传模式下,80%的MAB21L2杂合致病变异(20/25)和100%的MAB21L1杂合致病变异(25/25)发生在氨基酸49-52区域,导致小眼无眼或眼缺损异常(microphthalmia,anophthalmia or coloboma,MAC);携带该区域MAB21L2基因杂合突变的患者除MAC外,部分还伴骨骼关节发育异常(12/24,50%);杂合截短变异发生在MAB21L2基因可导致MAC(5/5,100%),而发生在MAB21L1则不致病。结论:在2个小眼畸形家系中发现了MAB21L2基因1个新致病变异和1个已知热点致病变异,通过文献综述比较和总结了MAB21L1和MAB21L2基因的突变频谱以及基因型-表型相互关系,为此类基因缺陷导致遗传病的诊断和鉴别诊断提供依据。展开更多
Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) chann...Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) channels. It consists of a line-of-sight(Lo S) and non-line-of-sight(NLo S) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e.the temporal autocorrelation function(ACF) and spatial cross correlation function(CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.展开更多
This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the ...This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the intensity levels, the open-access R-studio software was used based on the General Extreme Value (GEV) distribution function. Among the four linear parameter models adopted for integrating time as a covariate, the fourth linear model incorporating scale and location with the shape function constant produced the least corrected Akaike Information Criteria (AICc), varying between 306.191 to 101.497 for 15 and 1440 minutes, respectively, selected for calibration of the GEV distribution equation. The non-stationary intensities yielded higher values above those of stationary models, proving that the assumption of stationary IDF models underestimated extreme events. The difference of 13.71 mm/hr (22.71%) to 14.26 mm/hr (17.0%) intensities implies an underestimation of the peak flood from a stationary IDF curve. The statistical difference at a 95% confidence level between stationary and non-stationary models was significant, confirming evidence of climatic change influenced by time-variant parameters. Consequently, emphasis should be on applying shorter-duration storms for design purposes occurring with higher intensities to help reduce the flood risk and resultant infrastructural failures.展开更多
Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional...Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.展开更多
文摘目的:总结MAB21L2基因的变异和临床特点,并与高度同源的MAB21L1基因进行比较。方法:对中山眼科中心临床基因数据库中MAB21L2基因变异患者进行基因型和表型分析,回顾性分析既往文献报道的MAB21L2基因和高度同源基因MAB21L1变异的表型-基因型的关系。结果:在2个小眼畸形家系中发现2个MAB21L2基因杂合变异:先证者1携带已知变异c.151C>G/p.(Arg51Gly),患者双眼小眼畸形伴虹膜脉络膜缺损,伴骨关节屈曲。母亲携带相同杂合变异但表型正常;先证者2携带未报道的变异c.1042G>T/p.(Glu348*),左眼小眼畸形,右眼正常且无全身异常。结合文献回顾发现,在显性遗传模式下,80%的MAB21L2杂合致病变异(20/25)和100%的MAB21L1杂合致病变异(25/25)发生在氨基酸49-52区域,导致小眼无眼或眼缺损异常(microphthalmia,anophthalmia or coloboma,MAC);携带该区域MAB21L2基因杂合突变的患者除MAC外,部分还伴骨骼关节发育异常(12/24,50%);杂合截短变异发生在MAB21L2基因可导致MAC(5/5,100%),而发生在MAB21L1则不致病。结论:在2个小眼畸形家系中发现了MAB21L2基因1个新致病变异和1个已知热点致病变异,通过文献综述比较和总结了MAB21L1和MAB21L2基因的突变频谱以及基因型-表型相互关系,为此类基因缺陷导致遗传病的诊断和鉴别诊断提供依据。
基金supported by the National Natural Science Foundation of China,No.62271250the National Key Scientific Instrument and Equipment Development Project,No.61827801+3 种基金Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry),No.BE2022067,BE2022067-1 and BE2022067-3the Natural Science Foundation of Jiangsu Province,No.BK20211182the open research fund of National Mobile Communications Research Laboratory,Southeast University,No.2022D04the Experimental technology research and development,No.SYJS202304Z。
文摘Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) channels. It consists of a line-of-sight(Lo S) and non-line-of-sight(NLo S) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e.the temporal autocorrelation function(ACF) and spatial cross correlation function(CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.
文摘This study aims at establishing if climate change exists in the Niger Delta environment using non-stationary rainfall Intensity-Duration-Frequency (IDF) modelling incorporating time-variant parameters. To compute the intensity levels, the open-access R-studio software was used based on the General Extreme Value (GEV) distribution function. Among the four linear parameter models adopted for integrating time as a covariate, the fourth linear model incorporating scale and location with the shape function constant produced the least corrected Akaike Information Criteria (AICc), varying between 306.191 to 101.497 for 15 and 1440 minutes, respectively, selected for calibration of the GEV distribution equation. The non-stationary intensities yielded higher values above those of stationary models, proving that the assumption of stationary IDF models underestimated extreme events. The difference of 13.71 mm/hr (22.71%) to 14.26 mm/hr (17.0%) intensities implies an underestimation of the peak flood from a stationary IDF curve. The statistical difference at a 95% confidence level between stationary and non-stationary models was significant, confirming evidence of climatic change influenced by time-variant parameters. Consequently, emphasis should be on applying shorter-duration storms for design purposes occurring with higher intensities to help reduce the flood risk and resultant infrastructural failures.
基金Aeronautical Science Foundation of China (20071551016)
文摘Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.
