An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady sta...An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady state index based on chaotic theory and least squares support vector machine (LSSVM) is proposed in this paper. At first, the phase space reconstruction of original power quality data is performed to form a new data space containing the attractor. The new data space is used as training samples for the LSSVM. Then in order to predict power quality steady state index accurately, the particle swarm algorithm is adopted to optimize parameters of the LSSVM model. According to the simulation results based on power quality data measured in a certain distribution network, the model applies to several indexes with higher forecasting accuracy and strong practicability.展开更多
Carotid angioplasty and stenting (CAS) was developed to be a less invasive and complex procedure compared to carotid endarterectomy (CEA). It has emerged as an alternative for patients who are considered to have high ...Carotid angioplasty and stenting (CAS) was developed to be a less invasive and complex procedure compared to carotid endarterectomy (CEA). It has emerged as an alternative for patients who are considered to have high surgical risks due to medical comorbidities or anatomical high-risk features [1]. The procedure is usually done under local anesthesia with light sedation, with the subsequent expectation of less neurologic injury, venous thromboembolisms, and myocardial infarctions—all well-known clinical risks of undergoing surgical procedures under general anesthesia. CAS, however, carries some increased risks of arterial dissection, dislocation of atherothrombotic debris and embolization to the brain or eye, late embolization due to thrombus formation on the damaged plaque, and bradycardia and hypotension as a result of carotid sinus stimulation. Electroencephalography can detect cerebral ischemia and hypoxia along with measuring hypnotic effects, but has not been reported to be used during CAS to signal impending neurological deficit and allow for intervention to prevent stroke. We report on the use of patient state index (PSI), an electroencephalographic (EEG) derived variable used by SEDLine monitor (Masimo Inc., San Diego, CA) to monitor changes in cerebral blood flow during carotid angioplasty and stenting in an awake patient under local anesthesia. PSI was developed to measure the level of hypnosis and sedation during anesthesia and in the ICU. The PSI is based on quantitative electroencephalogram features, recorded from anterior and posterior scalp sites, as input to a multivariate algorithm that quantifies the most probable level of anesthesia or sedation. The PSI is reported as a range from 0 to 100, with decreasing values indicating increasing levels of anesthesia or sedation. Adequate depth of anesthesia is reflected by PSI value of 25 - 50, and a fully awake state by a PSI of 100 [2]. Other EEG analysis techniques have been explored to detect changes in cerebral blood flow during carotid surgery [3], such as entropy described by Khan and Ozcan in his recent work entitled Disagreement in Bilateral State Entropy Values in Carotid Artery Disease [4], but there are no previous reports of the use of PSI during procedural sedation in carotid angioplasty and stenting in an awake patient.展开更多
The objective is to develop an approach for the determination of the target reliability index for serviceability limit state(SLS) of single piles. This contributes to conducting the SLS reliability-based design(RBD) o...The objective is to develop an approach for the determination of the target reliability index for serviceability limit state(SLS) of single piles. This contributes to conducting the SLS reliability-based design(RBD) of piles. Based on a two-parameter,hyperbolic curve-fitting equation describing the load-settlement relation of piles, the SLS model factor is defined. Then, taking into account the uncertainties of load-settlement model, load and bearing capacity of piles, the formula for computing the SLS reliability index(βsls) is obtained using the mean value first order second moment(MVFOSM) method. Meanwhile, the limit state function for conducting the SLS reliability analysis by the Monte Carlo simulation(MCS) method is established. These two methods are finally applied to determine the SLS target reliability index. Herein, the limiting tolerable settlement(slt) is treated as a random variable. For illustration, four load test databases from South Africa are compiled again to conduct reliability analysis and present the recommended target reliability indices. The results indicate that the MVFOSM method overestimates βsls compared to that computed by the MCS method. Besides, both factor of safety(FS) and slt are key factors influencing βsls, so the combination of FS and βsls is welcome to be used for the SLS reliability analysis of piles when slt is determined. For smaller slt, pile types and soils conditions have significant influence on the SLS target reliability indices; for larger slt, slt is the major factor having influence on the SLS target reliability indices. This proves that slt is the most key parameter for the determination of the SLS target reliability index.展开更多
Mapping ecological states in semi-arid rangelands is crucial for effective land management and conservation efforts because it identifies difference in the ecological conditions across a landscape. This study presents...Mapping ecological states in semi-arid rangelands is crucial for effective land management and conservation efforts because it identifies difference in the ecological conditions across a landscape. This study presents an innovative approach for mapping two ecological states, Large Shrub Grass (LSG) and Large Shrub Eroded (LSE), within the Sandy Loam Upland and Deep (SLUD) ecological sites using a combination of drone and satellite data. The methodology leverages the Largest Patch Index (LPI) as a proxy metric to estimate eroded areas and classify ecological states. The integration of unmanned aerial vehicle (UAV) data with satellite-based remote sensing provides a scalable approach that can benefit various stakeholders involved in rangeland management. The study demonstrates the potential of this methodology by generating spatial layers at the landscape scale to inform on the state of rangeland ecosystems. The workflow showcases the power of remote sensing technology to map ecological states and addresses limitations in spatial coverage by integrating UAV and satellite data. By utilizing the bare ground LPI metric, which indicates the connectedness of bare ground, the methodology enables the classification of ecological states at a regional scale. This cost-effective approach potentially offers a standardized and reproducible method applicable across different sites and regions. The accuracy of the classification process is evaluated by comparing the results to ground-based polygons, dirt roads, and water locations. While the model performs well in identifying eroded areas, misclassifications occur in regions with mixed vegetation cover or low biomass. Future research should focus on incorporating temporal information from historical remote sensing archives to improve understanding of ecological state dynamics. Additionally, validation efforts can be enhanced by incorporating more ground-truth data and testing the methodology in diverse rangeland areas. The workflow serves as a blueprint for scaling up ecological states mapping in similar semi-arid rangelands. Further work should involve refining the approach through additional validation and exploring new remote sensing datasets. The methodology can be replicated in other regions to inform land management decisions, promote sustainable resource use, and advance the field of ecological states mapping.展开更多
本文设计了由不对称半圆柱对阵列组成的全介质超构表面,获得了两个高品质因子的准连续域束缚态模式(quasi-bound states in the continuum,QBIC).通过选择不同形式的对称破缺,在近红外频段均可产生两个稳健的QBIC,并且二者的谐振波长、...本文设计了由不对称半圆柱对阵列组成的全介质超构表面,获得了两个高品质因子的准连续域束缚态模式(quasi-bound states in the continuum,QBIC).通过选择不同形式的对称破缺,在近红外频段均可产生两个稳健的QBIC,并且二者的谐振波长、品质因子、偏振依赖等表现出不同的特性.模拟计算表明,通过测量两个QBIC的谐振波长,能够实现折射率和温度的双参数传感;通过调节不对称参数,利用QBIC的品质因子依赖于不对称参数的二次方反比关系,理论上能够提高品质因子到任意的数值,从而实现传感性能的提升和调节.该超构表面的折射率传感灵敏度、品质因子和优值分别达到194.7 nm/RIU,45829和8197,其温度传感灵敏度达到24 pm/℃.展开更多
Based on the characteristics of atom types, Hall＇s electrotopological state indices （En） are calculated for 165 nonionic organic compounds. On the basis of the characteristics of substituent and conjugated matrix, ...Based on the characteristics of atom types, Hall＇s electrotopological state indices （En） are calculated for 165 nonionic organic compounds. On the basis of the characteristics of substituent and conjugated matrix, a novel molecular structure parameter （G） is defined and calculated for 165 molecules in this paper. En and G show good structural selectivity for organic molecules. G, a satisfactory relationship between bioconcentration factor （BCF） and En, is expressed as： 1gBCF = -0.283 ＋ 1.246G ＋ 0.079E42 ＋ 0.351E9- 0.063E17 （n＇ = 122, R = 0.967, F = 425.636, s = 0.394）, which could provide estimation and prediction for the lgBCF of nonionic organic chemicals. Furthermore, the model is examined to validate overall robustness with Jackknife tests, and the independent variables in model do not exist cross correlation with VIF. All these regression results show that the new parameter G and electrotopological state index have good rationality and efficiency. It is concluded that the En and G will be used widely in quantitative structure-property/activity relationship （QSPR/QSAR） research.展开更多
文摘An effective power quality prediction for regional power grid can provide valuable references and contribute to the discovering and solving of power quality problems. So a predicting model for power quality steady state index based on chaotic theory and least squares support vector machine (LSSVM) is proposed in this paper. At first, the phase space reconstruction of original power quality data is performed to form a new data space containing the attractor. The new data space is used as training samples for the LSSVM. Then in order to predict power quality steady state index accurately, the particle swarm algorithm is adopted to optimize parameters of the LSSVM model. According to the simulation results based on power quality data measured in a certain distribution network, the model applies to several indexes with higher forecasting accuracy and strong practicability.
文摘Carotid angioplasty and stenting (CAS) was developed to be a less invasive and complex procedure compared to carotid endarterectomy (CEA). It has emerged as an alternative for patients who are considered to have high surgical risks due to medical comorbidities or anatomical high-risk features [1]. The procedure is usually done under local anesthesia with light sedation, with the subsequent expectation of less neurologic injury, venous thromboembolisms, and myocardial infarctions—all well-known clinical risks of undergoing surgical procedures under general anesthesia. CAS, however, carries some increased risks of arterial dissection, dislocation of atherothrombotic debris and embolization to the brain or eye, late embolization due to thrombus formation on the damaged plaque, and bradycardia and hypotension as a result of carotid sinus stimulation. Electroencephalography can detect cerebral ischemia and hypoxia along with measuring hypnotic effects, but has not been reported to be used during CAS to signal impending neurological deficit and allow for intervention to prevent stroke. We report on the use of patient state index (PSI), an electroencephalographic (EEG) derived variable used by SEDLine monitor (Masimo Inc., San Diego, CA) to monitor changes in cerebral blood flow during carotid angioplasty and stenting in an awake patient under local anesthesia. PSI was developed to measure the level of hypnosis and sedation during anesthesia and in the ICU. The PSI is based on quantitative electroencephalogram features, recorded from anterior and posterior scalp sites, as input to a multivariate algorithm that quantifies the most probable level of anesthesia or sedation. The PSI is reported as a range from 0 to 100, with decreasing values indicating increasing levels of anesthesia or sedation. Adequate depth of anesthesia is reflected by PSI value of 25 - 50, and a fully awake state by a PSI of 100 [2]. Other EEG analysis techniques have been explored to detect changes in cerebral blood flow during carotid surgery [3], such as entropy described by Khan and Ozcan in his recent work entitled Disagreement in Bilateral State Entropy Values in Carotid Artery Disease [4], but there are no previous reports of the use of PSI during procedural sedation in carotid angioplasty and stenting in an awake patient.
基金Projects(51278216,51308241)supported by the National Natural Science Foundation of ChinaProject(2013BS010)supported by the Funds of Henan University of Technology for High-level Talents,China
文摘The objective is to develop an approach for the determination of the target reliability index for serviceability limit state(SLS) of single piles. This contributes to conducting the SLS reliability-based design(RBD) of piles. Based on a two-parameter,hyperbolic curve-fitting equation describing the load-settlement relation of piles, the SLS model factor is defined. Then, taking into account the uncertainties of load-settlement model, load and bearing capacity of piles, the formula for computing the SLS reliability index(βsls) is obtained using the mean value first order second moment(MVFOSM) method. Meanwhile, the limit state function for conducting the SLS reliability analysis by the Monte Carlo simulation(MCS) method is established. These two methods are finally applied to determine the SLS target reliability index. Herein, the limiting tolerable settlement(slt) is treated as a random variable. For illustration, four load test databases from South Africa are compiled again to conduct reliability analysis and present the recommended target reliability indices. The results indicate that the MVFOSM method overestimates βsls compared to that computed by the MCS method. Besides, both factor of safety(FS) and slt are key factors influencing βsls, so the combination of FS and βsls is welcome to be used for the SLS reliability analysis of piles when slt is determined. For smaller slt, pile types and soils conditions have significant influence on the SLS target reliability indices; for larger slt, slt is the major factor having influence on the SLS target reliability indices. This proves that slt is the most key parameter for the determination of the SLS target reliability index.
文摘Mapping ecological states in semi-arid rangelands is crucial for effective land management and conservation efforts because it identifies difference in the ecological conditions across a landscape. This study presents an innovative approach for mapping two ecological states, Large Shrub Grass (LSG) and Large Shrub Eroded (LSE), within the Sandy Loam Upland and Deep (SLUD) ecological sites using a combination of drone and satellite data. The methodology leverages the Largest Patch Index (LPI) as a proxy metric to estimate eroded areas and classify ecological states. The integration of unmanned aerial vehicle (UAV) data with satellite-based remote sensing provides a scalable approach that can benefit various stakeholders involved in rangeland management. The study demonstrates the potential of this methodology by generating spatial layers at the landscape scale to inform on the state of rangeland ecosystems. The workflow showcases the power of remote sensing technology to map ecological states and addresses limitations in spatial coverage by integrating UAV and satellite data. By utilizing the bare ground LPI metric, which indicates the connectedness of bare ground, the methodology enables the classification of ecological states at a regional scale. This cost-effective approach potentially offers a standardized and reproducible method applicable across different sites and regions. The accuracy of the classification process is evaluated by comparing the results to ground-based polygons, dirt roads, and water locations. While the model performs well in identifying eroded areas, misclassifications occur in regions with mixed vegetation cover or low biomass. Future research should focus on incorporating temporal information from historical remote sensing archives to improve understanding of ecological state dynamics. Additionally, validation efforts can be enhanced by incorporating more ground-truth data and testing the methodology in diverse rangeland areas. The workflow serves as a blueprint for scaling up ecological states mapping in similar semi-arid rangelands. Further work should involve refining the approach through additional validation and exploring new remote sensing datasets. The methodology can be replicated in other regions to inform land management decisions, promote sustainable resource use, and advance the field of ecological states mapping.
文摘本文设计了由不对称半圆柱对阵列组成的全介质超构表面,获得了两个高品质因子的准连续域束缚态模式(quasi-bound states in the continuum,QBIC).通过选择不同形式的对称破缺,在近红外频段均可产生两个稳健的QBIC,并且二者的谐振波长、品质因子、偏振依赖等表现出不同的特性.模拟计算表明,通过测量两个QBIC的谐振波长,能够实现折射率和温度的双参数传感;通过调节不对称参数,利用QBIC的品质因子依赖于不对称参数的二次方反比关系,理论上能够提高品质因子到任意的数值,从而实现传感性能的提升和调节.该超构表面的折射率传感灵敏度、品质因子和优值分别达到194.7 nm/RIU,45829和8197,其温度传感灵敏度达到24 pm/℃.
基金the State Key Laboratory of Pollution Control and Reuse of China Project Proposal (PCRRF07009)the University Natural Science Foundation of Jiangsu Province (05KJD150221)Natural Science Incubation Foundation of Xuzhou Normal University (05PLY04)
文摘Based on the characteristics of atom types, Hall＇s electrotopological state indices （En） are calculated for 165 nonionic organic compounds. On the basis of the characteristics of substituent and conjugated matrix, a novel molecular structure parameter （G） is defined and calculated for 165 molecules in this paper. En and G show good structural selectivity for organic molecules. G, a satisfactory relationship between bioconcentration factor （BCF） and En, is expressed as： 1gBCF = -0.283 ＋ 1.246G ＋ 0.079E42 ＋ 0.351E9- 0.063E17 （n＇ = 122, R = 0.967, F = 425.636, s = 0.394）, which could provide estimation and prediction for the lgBCF of nonionic organic chemicals. Furthermore, the model is examined to validate overall robustness with Jackknife tests, and the independent variables in model do not exist cross correlation with VIF. All these regression results show that the new parameter G and electrotopological state index have good rationality and efficiency. It is concluded that the En and G will be used widely in quantitative structure-property/activity relationship （QSPR/QSAR） research.
