The transmission line is one vital component of electrical power system. It determines some fundamental characteristics such as transmission efficiencies, voltage drops and line losses which are ...important matters to be considered in system planning, design and maintaining. The so-called PI-based modeling refers to using basic PI (proportional and integral) elements as well as other basic elements to implement one specific simulation. Grounded on the distributed-element model and addressing complex-element modeling, one PI-based simulation method is introduced in this study for teaching purposes and applied to modeling and simulation for performance testing of the power transmission line. The proposed method is demonstrated in the Simulink simulation environment and verified by performance testing of the power transmission line including complex-element-based equivalent distributed-element modeling for (short, medium and long) transmission lines, load flow analysis, short circuit test, open circuit test and the “Ferranti-effect” phenomenon, SIL (surge impedance loading) and series and shunt compensation simulation. Results indicate workability of the proposed method that it provides one convenient and vivid way for complex-element-based simulation modeling and solving numerical solutions as well. The proposed PI-based method for complex-element modeling and its Simulink-based simulation approach may be useful for related electrical engineering simulations and testing.
•Only basic PI (proportional and integral) elements and other basic elements are employed for complex-element modeling.•Applied to modeling and simulation for performance testing of the power transmission line.•PI-based complex-element modeling method with simulation results may be useful for related electrical engineering simulation and testing.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Schizophrenia is a severe mental disorder characterized by impaired perception, delusions, thought disorder, abnormal emotion regulation, altered motor function, and impaired drive. The default mode ...network （DMN）, since it was first proposed in 2001, has become a central research theme in neuropsychiatric disorders, including schizophrenia. In this review, first we define the DMN and describe its functional activity, functional and anatomical connectivity, heritability, and inverse correlation with the task positive network. Second, we review empirical studies of the anatomical and functional DMN, and anti-correlation between DMN and the task positive network in schizophrenia. Finally, we review preliminary evidence about the relationship between antipsychotic medications and regulation of the DMN, review the role of DMN as a treatment biomarker for this disease, and consider the DMN effects of individualized therapies for schizophrenia.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The objective of this study is to propose a position-distance-related model based on complex networks for the H1N1 epidemic simulation. Situation updates of the H1N1 prevalenced in 2009 show that ...spreading of the epidemic virus is highly correlative with its position and distance as well. Then in the proposed simulation model, each node in the network is described with not only its edges but also its position and distance. Accordingly, two mechanisms called "growth with position" and "degree and distance based preferential attachment" are introduced in the proposed model that it establishes one connection with likelihood proportional to node's degree and inversely proportional to the distance between two nodes. Beside the traditional node-growth mode, one called link-growth mode is also introduced. The main advantage of the proposed method is that it is one concise data-driven modeling based on complex networks. Simulation results utilizing the proposed link-growth mode and the traditional node-growth mode show that the two modes are equivalent to each other but from different perspectives. Moreover, compared to the traditional node-growth mode, the proposed link-growth mode is clear and concise.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
In pattern recognition, patterns are described in terms of features. The features form feature vectors in the feature space. In the light of the phenomenon of gravitation in star clusters, we define ...patterns in the feature space to self-organize into clustering networks called “vector gravitation clustering networks” in this study. In the proposed clustering method, one called “vector gravitational force” is employed for the similarity measure in the feature space. Then by means of the “vector gravitational force”, patterns self-organize clustering networks called “vector gravitation clustering networks” in the feature space. The proposed clustering method is applied to experiments. The experimental results show workability of the proposed clustering method. It is revealed that patterns tend to have more called “vector gravitational force” between ones of the same categories than between ones of the different categories in the feature space. Finally, further performance analysis employing the ANOVA (“analysis of variance”) and the Newman-Keul procedure indicates potentiality of the proposed clustering method. As being inspired by the phenomenon of gravitation in star clusters and by using the “vector gravitational force” for similarity measure, “interpretability” is one obvious advantage of the proposed clustering method, and it may be viewed as one natural clustering method.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Water-level fluctuation evaluation and forecasting for a river is increasingly important because of its close ties to human living and production. In this study, with annual periodic extension for ...monthly average water-level fluctuation, Fourier analysis employing finite Fourier series is presented for evaluating its fluctuation. Fourier analysis in the conventional form which is the most common analysis method in the frequency domain, however, cannot be straightly applied for forecasting. Then, the extended version of the Fourier-series model in the least-square sense is proposed for forecasting. The extended forecasting model obtains its optimum Fourier coefficients in the least-squares based on previous monthly water-level observations. Experiments at the different monitoring stations of the Yangtze River in China indicate potentiality of the proposed method. It is shown that the fluctuation of monthly average water-level is well described by about six-term harmonics. And the extended Fourier forecasting model predicts the fluctuation of monthly water level most fitting about three-term harmonics.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•A finite Fourier-series-based model for evaluating hourly RH fluctuation.•Apply its least-squares-extended model for predicting the RH fluctuation.•Spectrum characteristics and conjugate symmetry ...property for modeling.•Daily 24-hour RH fluctuation is well described by 12-term harmonics.•Less than 6-term harmonics for forecasting the RH fluctuation.
Air humidity is one important measurement parameter involved in a wide range of fields of science and engineering. This study addresses Fourier-series-based evaluation and prediction of hourly ambient air humidity fluctuation. It is shown that hourly ambient humidity fluctuation displays a significant 24-hour cyclical variation. Then on the basis of daily periodic extension for hourly ambient air humidity fluctuation, a finite Fourier-series-based evaluation model is introduced for describing its hourly fluctuation. The Fourier-based analysis in its conventional form, however, cannot be straightly applicable to prediction. Then in combination with the least-squares method for coefficient-seeking based on finite observations of hourly air humidity, the extended version of the Fourier-series model in the least-squares is proposed for forecasting. The proposed Fourier-series-based method is applied to experiments of evaluating and forecasting hourly air humidity fluctuations at different monitoring stations with satisfying results. The experimental results, further mathematical analysis of the conjugate symmetry property and spectrum characteristic analysis for the Fourier-series involved in the Fourier-based model indicate that daily 24-hour air humidity fluctuation is well described by about 12-term harmonics and the extended Fourier-series forecasting model predicts the hourly humidity fluctuation best fitting with less than 6-term harmonics.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Water-level is one of the critical parameters for a river. It has a close relation to human living & production and socio-economic sustainability development. WLF (water-level fluctuation) evaluation ...and forecasting for a river is then becoming increasingly important. For water resource planning and management, traditionally, mathematical models are separately developed and designed for sectorial applications. As predictions utilizing more different forecast variables require additional efforts and costs to acquire and predict the variables, advantages of time-series-based or data-driven modeling lie on its conciseness and good performance even higher accuracy. The Fourier-based analysis technology is a classical tool widely used for time-series analysis. However, the Fourier-related approach in its conventional form is not directly applicable to prediction. Addressing hourly WLF prediction from the viewpoint of time-series analysis, a called DCT-LS-extended (“discrete cosine transform (DCT)-based least-squares-extended”) forecast model is presented in this study. The DCT coefficients for the proposed DCT-based forecast modeling are determined in the least-squares sense on the basis of previous hourly WLF observations. Experiments at hydrological monitoring stations in the XiangJiang River of China yield stultifying results. Potentiality of the proposed method is demonstrated by further analysis. The proposed DCT-LS-extended model forecasts hourly WLFs best fitting with less than 12-term DCT coefficients. The proposed method may benefit other applications.
Electric load movement analysis is an important task for effective operation and planning of power systems. It is shown that a weekly quasi-periodicity is enclosed in electric daily peak load ...movement. On the basis of weekly periodic extension for electric daily peak load movement, the so-called elliptic-orbit model is introduced to describe its movement. Electric daily peak load movement as time series is mapped into the polar coordinates to form the elliptic-orbit model, in which each 7-day-movement is depicted as one elliptic orbit. Experimental results of the Great Britain National Grid and Analysis indicate workability and effectiveness of the proposed method. It is shown that the electric daily peak load movement with weekly periodic extension is well described by the elliptic-orbit model, which presents a vivid description for analysing electric daily peak load movement in a concise and intuitive way, and others may benefit from it.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Electric load forecasting is essential to economic operation and power system control in the electric power industry. Modelling and forecasts for different time horizons are of increasingly ...importance for different operations. Discrete cosine transform (DCT) is one Fourier-related computational technique. It is widely used in signal and image processing for its remarkable characteristics on optimal decorrelation and energy compaction. From time-series analysis perspective, this study proposes a DCT-based predictive model for forecasting hourly load movement. Based on finite hourly load observations, the proposed DCT-based predictive model combines with the least-squares approach to get the optimum DCT coefficients, which are approximated in the least-squares sense. Then the obtained least-squares-optimum DCT coefficients are employed for forecast modelling to predict the load future movement. Experimental results and analysis show workability of the proposed forecast modelling. It is indicated that the DCT-based least-squares predictive model predicts hourly load movement most fitting with about 12-term DCT coefficients.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Metal clusters, such as iron-sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins. Herein we report the formation and crystal structure ...of a planar square tetranuclear silver cluster when silver ions were mixed with human copper chaperone Atox1. Quantum chemical studies reveal that two Ag 5s
1
electrons in the tetranuclear silver cluster fully occupy the one bonding molecular orbital, with the assumption that this Ag
4
cluster is Ag
4
2+
, leading to extensive electron delocalization over the planar square and significant stabilization. This bonding pattern of the tetranuclear silver cluster represents an aromatic all-metal structure that follows a 4
n
+ 2 electron counting rule (
n
= 0). This is the first time an all-metal aromatic silver cluster was observed in a protein.
Metal clusters, such as iron-sulfur clusters, play key roles in sustaining life and are intimately involved in the functions of metalloproteins.
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IJS, KILJ, NUK, UL, UM, UPUK
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