In this paper,we give all-sided pastic analysis of the rectangular slab with three edges simply-supported and other free.Here we discuss the following four cases:(1)The uniformly distributedload over the area a slab.(...In this paper,we give all-sided pastic analysis of the rectangular slab with three edges simply-supported and other free.Here we discuss the following four cases:(1)The uniformly distributedload over the area a slab.(2).A concentrated load act at midpoint of free edges slab.(3)A concen-trated load act at the center a slab.(4)The line load act along free edge of slab.展开更多
Presented in this manuscript are conventional electrical engineering tools to model the earth as a rotating electrical machine. Calculations using known parameters of the earth and measured field data has resulted in ...Presented in this manuscript are conventional electrical engineering tools to model the earth as a rotating electrical machine. Calculations using known parameters of the earth and measured field data has resulted in new understanding of the earth’s electrical system and gyroscopic rotation. The material makeup of the inner earth is better understood based on derived permeability and permittivity constants. The planet has been modeled as simple coils and then as a parallel impedance circuit which has led to fundamental insight into planetary speed control and RLC combination for Schumann Resonance of 7.83 Hz. Torque and Voltage Constants and the inverse Speed Constant are calculated using three methods and all compare favorably with Newton’s Gravitational Constant. A helical resonator is referenced and Schumann’s Resonant ideal frequency is calculated and compared with others idealism. A new theory of gravity based on particle velocity selector at the poles is postulated. Two equations are presented as the needed links between Faraday’s electromagnetism and Newtonian physics. Acceleration and Deceleration of earth is explained as a centripetal governor. A new equation for planetary attraction and the attraction of atomic matter is theorized. Rotation of the earth’s electrical coil is explained in terms of the Richardson effect. Electric power transfer from the sun to the planets is proposed via Flux Transfer Events. The impact of this evolving science of electromagnetic modeling of planets will be magnified as the theory is proven, and found to be useful for future generations of engineers and scientists who seek to discover our world and other planets.展开更多
The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum...The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.展开更多
Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients a...Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.展开更多
AIM:rAAV mediated endostatin gene therapy has been examined as a new method for treating cancer.However, a sustained and high protein delivery is required to achieve the desired therapeutic effects.We evaluated the im...AIM:rAAV mediated endostatin gene therapy has been examined as a new method for treating cancer.However, a sustained and high protein delivery is required to achieve the desired therapeutic effects.We evaluated the impact of topoisomerase inhibitors in rAAV delivered endostatin gene therapy in a liver tumor model. METHODS:rAAV containing endostatin expression cassettes were transduced into hepatoma cell lines.To test whether the topoisomerase inhibitor pretreatment increased the expression of endostatin,Western blotting and ELISA were performed.The biologic activity of endostatin was confirmed by endothelial cell proliferation and tube formation assays. The anti-tumor effects of the rAAV-endostatin vector combined with a topoisomerase inhibitor,etoposide,were evaluated in a mouse liver tumor model. RESULTS:Topoisomerase inhibitors,including camptothecin and etoposide,were found to increase the endostatin exPression level in vitro.The over-expressed endostatin, as a result of pretreatment with a topoisomerase inhibitor, was also biologically active.In animal experiments,the combined therapy of topoisomerase inhibitor,etoposide with the rAAV-endostatin vector had the best tumor- suppressive effect and tumor foci were barely observed in livers of the treated mice.Pretreatment with an etoposide increased the level of endostatin in the liver and serum of rAAV-endostatin treated mice.Finally,the mice treated With rAAV-endostatin in combination with etoposide showed the longest survival among the experimental models. CONCLUSION:rAAV delivered endostatin gene therapy in combination with a topoisomerase inhibitor pretreatment is an effective modality for anticancer gene therapy.展开更多
提出了一种基于最小二乘支持向量机的织物剪切性能预测模型,并且采用遗传算法进行最小二乘支持向量机的参数优化,将获得的样本进行归一化处理后,将其输入预测模型以得到预测结果.仿真结果表明,基于最小二乘支持向量机的预测模型比BP神...提出了一种基于最小二乘支持向量机的织物剪切性能预测模型,并且采用遗传算法进行最小二乘支持向量机的参数优化,将获得的样本进行归一化处理后,将其输入预测模型以得到预测结果.仿真结果表明,基于最小二乘支持向量机的预测模型比BP神经网络和线性回归方法具有更高的精度和范化能力.
Abstract：
A new method is proposed to predict the fabric shearing property with least square support vector machines ( LS-SVM ). The genetic algorithm is investigated to select the parameters of LS-SVM models as a means of improving the LS- SVM prediction. After normalizing the sampling data, the sampling data are inputted into the model to gain the prediction result. The simulation results show the prediction model gives better forecasting accuracy and generalization ability than BP neural network and linear regression method.展开更多
The beneficial acclimation hypothesis (BAH) predicts that animals acclimated to a particular temperature have enhanced performance or fitness at that temperature in comparison with animals acclimated to other temperat...The beneficial acclimation hypothesis (BAH) predicts that animals acclimated to a particular temperature have enhanced performance or fitness at that temperature in comparison with animals acclimated to other temperatures. The BAH has been tested by a variety of empirical examinations, and was rejected by some of them. In order to provide new evidences for the BAH, the effects of acute and acclimation temperature (AT) on locomotor performance of Macrobiotus hufelandi (Tardigrada: Macrobiotidae) were investigated. The tardigrades were collected from Nanwutai, Qinling Mountains which traverse from west to east in central China. The subjects were acclimated to either 2℃ or 22℃ for 2 weeks. The animal was transferred onto a frosted slide and allowed to walk freely at the performance temperature (PT) 2℃ or 22℃. Only one individual was tested per test bout, which lasted from three to five minutes. To avoid occurrence of thermal acclimation effect, the standard adaptation time was limited to 1.5 min. Each subject was tested for once at the same PT, and was tested only at one PT. A total of 25 individuals were tested and measured at the same PT. The locomotor performance of the animals was recorded with a digital video camera mounted on a microscope at 4×10 amplification and replayed on a PC. Every subject was identified. Walking speed (WS) and percentage of time moving (PTM) at both PTs (2℃ or 22℃) were selected as the rate parameters of locomotor performance. The two-way repeated measures ANOVA with a significance level of α= 0.05 and Duncan multiple range test were used to analyze the data. WS of the animals acclimated to and tested at the same temperatures was significantly faster than that for animals acclimated to and tested at the different temperatures, similarly, PTM of the animals acclimated to 22℃ and tested at 22℃ was significantly greater than PTM of animals acclimated to 22℃ and tested at 2℃, which indicated that the animals acclimated to a particular temperature have enhanced locomotor performance in that temperature relative to the animals acclimated to that temperature in other thermal environment. WS of the animals acclimated to 22℃ and tested at 22℃ was significantly faster than WS of animals acclimated to 2℃ and tested at 22℃, PTM of the animals acclimated to 22℃ and tested at 22℃ was significantly greater than PTM of animals acclimated to 2℃ and tested at 22℃. These results supported the BAH. It could be concluded that the PT and thermal acclimation as well as the interaction between the PT and AT significantly influence the locomotor performance of M.hufelandi, and that, despite the existence of a few results of this study that don’t support the BAH, some results of this study support for this hypothesis, and that the animals acclimated to a particular temperature have enhanced locomotor performance in that temperature relative to the animals acclimated to that temperature in other thermal environment, implying that any performance temperature that deviates from the acclimation temperature could cause the reduction of the walking speed which is closely related to the fitness of the M.hufelandi.展开更多
The present pagination reports both Brownian diffusion and thermophoresis aspects subject to magneto hydrodynamic Williamson fluid model.Assuming the flow is unsteady and blood is treated as Williamson fluid over a we...The present pagination reports both Brownian diffusion and thermophoresis aspects subject to magneto hydrodynamic Williamson fluid model.Assuming the flow is unsteady and blood is treated as Williamson fluid over a wedge with radiation.The governing equations are transformed into ordinary differential equations by using similarity variables.The analytical solutions of the transformed governing equations are obtained by using the RK 4th order method along with shooting technique solver.The effects of various physical parameters such as Hartmann number,local Weissenberg number,radiation parameter,unsteadiness parameter,Prandtl number,Lewis number,Brownian diffusion,thermophoresis,wedge angle parameter,moving wedge parameter,on velocity,temperature,concentration,skin friction,heat transfer rate and mass transfer rate have been discussed in detail.The velocity and temperature profile deprives for larger We and an opposite trend is observed for concentration.The radiation parameter is propositional to temperature and a counter behaviour is observed for Pr.展开更多
Switzerland is one of the most desirable European destinations for Chinese tourists;therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leadi...Switzerland is one of the most desirable European destinations for Chinese tourists;therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leading social media platform—Sina Weibo, a hybrid of Twitter and Facebook—has more than 600 million users. Weibo’s great market penetration suggests that tourism operators and markets need to understand how to build effective and sustainable communications on Chinese social media platforms. In order to offer a better decision support platform to tourism destination managers as well as Chinese tourists, we proposed a framework using linked data on Sina Weibo. Linked Data is a term referring to using the Internet to connect related data. We will show how it can be used and how ontology can be designed to include the users’ context (e.g., GPS locations). Our framework will provide a good theoretical foundation for further understand Chinese tourists’ expectation, experiences, behaviors and new trends in Switzerland.展开更多
Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using d...Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.展开更多
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
Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence t...Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.展开更多
Potassium-ion batteries(PIBs)are considered promising alternatives to lithium-ion batteries owing to cost-effective potassium resources and a suitable redox potential of-2.93 V(vs.-3.04 V for Li+/Li).However,the explo...Potassium-ion batteries(PIBs)are considered promising alternatives to lithium-ion batteries owing to cost-effective potassium resources and a suitable redox potential of-2.93 V(vs.-3.04 V for Li+/Li).However,the exploration of appro-priate electrode materials with the correct size for reversibly accommodating large K+ions presents a significant challenge.In addition,the reaction mecha-nisms and origins of enhanced performance remain elusive.Here,tetragonal FeSe nanoflakes of different sizes are designed to serve as an anode for PIBs,and their live and atomic-scale potassiation/depotassiation mechanisms are revealed for the first time through in situ high-resolution transmission electron micros-copy.We found that FeSe undergoes two distinct structural evolutions,sequen-tially characterized by intercalation and conversion reactions,and the initial intercalation behavior is size-dependent.Apparent expansion induced by the intercalation of K+ions is observed in small-sized FeSe nanoflakes,whereas unexpected cracks are formed along the direction of ionic diffusion in large-sized nanoflakes.The significant stress generation and crack extension originating from the combined effect of mechanical and electrochemical interactions are elucidated by geometric phase analysis and finite-element analysis.Despite the different intercalation behaviors,the formed products of Fe and K_(2)Se after full potassiation can be converted back into the original FeSe phase upon depotassiation.In particular,small-sized nanoflakes exhibit better cycling perfor-mance with well-maintained structural integrity.This article presents the first successful demonstration of atomic-scale visualization that can reveal size-dependent potassiation dynamics.Moreover,it provides valuable guidelines for optimizing the dimensions of electrode materials for advanced PIBs.展开更多
Poverty alleviation by supporting industry is a key measure to promote the poverty alleviation of relocated households. Taking Xundian County, the first county in Yunnan Province that has been lifted out of poverty, a...Poverty alleviation by supporting industry is a key measure to promote the poverty alleviation of relocated households. Taking Xundian County, the first county in Yunnan Province that has been lifted out of poverty, as an research case, this article analyzes and summarizes the industry-supporting poverty alleviation achievements and successful experience of two typical relocation areas (Shanhou Village and Eyang Village) in Xundian County. Practice has shown that the key to industry-supporting poverty alleviation lies in targetedness to strengthen the participation of poor farmers in industrial development. The interests of poverty alleviation entities should be linked by market mechanism to establish a benign interaction between all parties for win-win situation, thereby effectively guaranteeing the long-term and healthy development of poverty alleviation by supporting industry.展开更多
Nowadays, power quality issues are becoming a significant research topic because of the increasing inclusion of very sensitive devices and considerable renewable energy sources. In general, most of the previous power ...Nowadays, power quality issues are becoming a significant research topic because of the increasing inclusion of very sensitive devices and considerable renewable energy sources. In general, most of the previous power quality classification techniques focused on single power quality events and did not include an optimal feature selection process. This paper presents a classification system that employs Wavelet Transform and the RMS profile to extract the main features of the measured waveforms containing either single or complex disturbances. A data mining process is designed to select the optimal set of features that better describes each disturbance present in the waveform. Support Vector Machine binary classifiers organized in a “One Vs Rest” architecture are individually optimized to classify single and complex disturbances. The parameters that rule the performance of each binary classifier are also individually adjusted using a grid search algorithm that helps them achieve optimal performance. This specialized process significantly improves the total classification accuracy. Several single and complex disturbances were simulated in order to train and test the algorithm. The results show that the classifier is capable of identifying >99% of single disturbances and >97% of complex disturbances.展开更多
The seedlings of Vernicia montana derived from seeds soaking with water (the first group)or 300 mg5L -1 mixed nitric_acid rare earth solution (the second group) were treated with various concentrations of mixed nitric...The seedlings of Vernicia montana derived from seeds soaking with water (the first group)or 300 mg5L -1 mixed nitric_acid rare earth solution (the second group) were treated with various concentrations of mixed nitric_acid rare earth solution by foliage spraying. The results showed that the seedling heights sprayed with 100 和 1 000 mg·L -1 of the first group and with 50 和 100 mg·L -1 of the second group were significantly higher than the controls, and the diameter at ground level sprayed with 300 mg·L -1 of the second group was significantly greater than the control, being 26.92% more than the latter; except for spraying with 0 mg5L -1 and 700～1 500 mg5L -1 of the second group, the seedling dry weight above ground of others was 29.13%～73.91% greater than the control, whereas the seedling dry weight under ground of others was 20.78%～116.88% greater than the control; the contents of chlorophyll a and chlorophyll b for all spraying seedling were 91.67%～191.67% and 87.5%～306.25% greater than the control, respectively, and soluble proteins and soluble sugars were 16.00%～179.78% and 10.73%～105.65% greater than the control, respectively. Compared with the control, the activity of SOD tended to increase, whereas the contents of MDA decreased. These indicated that spraying leaves with optimum concentration of mixed nitric_acid rare earth solution could markedly promote the growth of seedlings and improve resistance ability of V. montana seedlings to bad environment. On the whole, the effects of spraying the leaves of seedling with 50～500 mg5L -1 mixed nitric_acid rare earth solution, which were derived from seeds soaking with 300 mg·L -1 mixed nitric_acid rare earth solution, were good.展开更多
Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BL...Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.展开更多
A new binuclear copper(Ⅱ) complex, [Cu2(phen)2(H2O)2( μ2-C2O4)](NO3)2, has been synthesized and characterized by elemental analysis, IR and UV-Vis spectrum. Its crystal structure was determined by single crystal X-r...A new binuclear copper(Ⅱ) complex, [Cu2(phen)2(H2O)2( μ2-C2O4)](NO3)2, has been synthesized and characterized by elemental analysis, IR and UV-Vis spectrum. Its crystal structure was determined by single crystal X-ray diffraction techniques. Crystal data: monoclinic, space group P21/c, a=0.712 21(8) nm, b=1.170 93(14) nm, c=1.783 7(2) nm, β=111.828(2)°, and V=1.380 8(3) nm3, Dc=1.769 Mg·m-3, Z=2, F(000)=744, R1=0.025 4, wR2=0.069 5, Gof=1.077, Δρ=328^-455 e·nm-3. The complex is packed by one centrosymmetry binuclear copper(Ⅱ) unit, oxalate dianion and NO3- anion. In the molecule structure of the title complex, two Cu(Ⅱ) ions are bridged by oxalate dianion and each Cu(Ⅱ) ions coordinates with two nitrogen atoms from 1,10-phenanthroline ligand and one oxygen atom from water to form a five-coordinate distorted square-pyramidal configuration. The hydrogen bonds are observed between coordinated water molecules and NO3- anions. The analysis of the crystal structure indicates that the complex has a two-dimensional stacking network structure, which is formed by intramolecular hydrogen bonds, intermolecular hydrogen bonds and stacking effect of aromatic ring. CCDC: 255345.展开更多
In this work, a total of 322 tests were taken on young volunteers by performing 10 different falls, 6 different Activities of Daily Living (ADL) and 7 Dynamic Gait Index (DGI) tests using a custom-designed Wireless Ga...In this work, a total of 322 tests were taken on young volunteers by performing 10 different falls, 6 different Activities of Daily Living (ADL) and 7 Dynamic Gait Index (DGI) tests using a custom-designed Wireless Gait Analysis Sensor (WGAS). In order to perform automatic fall detection, we used Back Propagation Artificial Neural Network (BP-ANN) and Support Vector Machine (SVM) based on the 6 features extracted from the raw data. The WGAS, which includes a tri-axial accelerometer, 2 gyroscopes, and a MSP430 microcontroller, is worn by the subjects at either T4 (at back) or as a belt-clip in front of the waist during the various tests. The raw data is wirelessly transmitted from the WGAS to a near-by PC for real-time fall classification. The BP ANN is optimized by varying the training, testing and validation data sets and training the network with different learning schemes. SVM is optimized by using three different kernels and selecting the kernel for best classification rate. The overall accuracy of BP ANN is obtained as 98.20% with LM and RPROP training from the T4 data, while from the data taken at the belt, we achieved 98.70% with LM and SCG learning. The overall accuracy using SVM was 98.80% and 98.71% with RBF kernel from the T4 and belt position data, respectively.展开更多
文摘In this paper,we give all-sided pastic analysis of the rectangular slab with three edges simply-supported and other free.Here we discuss the following four cases:(1)The uniformly distributedload over the area a slab.(2).A concentrated load act at midpoint of free edges slab.(3)A concen-trated load act at the center a slab.(4)The line load act along free edge of slab.
文摘Presented in this manuscript are conventional electrical engineering tools to model the earth as a rotating electrical machine. Calculations using known parameters of the earth and measured field data has resulted in new understanding of the earth’s electrical system and gyroscopic rotation. The material makeup of the inner earth is better understood based on derived permeability and permittivity constants. The planet has been modeled as simple coils and then as a parallel impedance circuit which has led to fundamental insight into planetary speed control and RLC combination for Schumann Resonance of 7.83 Hz. Torque and Voltage Constants and the inverse Speed Constant are calculated using three methods and all compare favorably with Newton’s Gravitational Constant. A helical resonator is referenced and Schumann’s Resonant ideal frequency is calculated and compared with others idealism. A new theory of gravity based on particle velocity selector at the poles is postulated. Two equations are presented as the needed links between Faraday’s electromagnetism and Newtonian physics. Acceleration and Deceleration of earth is explained as a centripetal governor. A new equation for planetary attraction and the attraction of atomic matter is theorized. Rotation of the earth’s electrical coil is explained in terms of the Richardson effect. Electric power transfer from the sun to the planets is proposed via Flux Transfer Events. The impact of this evolving science of electromagnetic modeling of planets will be magnified as the theory is proven, and found to be useful for future generations of engineers and scientists who seek to discover our world and other planets.
文摘The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.
基金Supported by The Agency for Healthcare Research and Quality,No.R18HS02420-01
文摘Clinical decision support(CDS) systems with automated alerts integrated into electronic medical records demonstrate efficacy for detecting medication errors(ME) and adverse drug events(ADEs). Critically ill patients are at increased risk for ME, ADEs and serious negative outcomes related to these events. Capitalizing on CDS to detect ME and prevent adverse drug related events has the potential to improve patient outcomes. The key to an effective medication safety surveillance system incorporating CDS is advancing the signals for alerts by using trajectory analyses to predict clinical events, instead of waiting for these events to occur. Additionally, incorporating cutting-edge biomarkers into alert knowledge in an effort to identify the need to adjust medication therapy portending harm will advance the current state of CDS. CDS can be taken a step further to identify drug related physiological events, which are less commonly included in surveillance systems. Predictive models for adverse events that combine patient factors with laboratory values and biomarkers are being established and these models can be the foundation for individualized CDS alerts to prevent impending ADEs.
基金Supported by a faculty research grant of Yonsei University College of Medicine for 2002,No.2002-06
文摘AIM:rAAV mediated endostatin gene therapy has been examined as a new method for treating cancer.However, a sustained and high protein delivery is required to achieve the desired therapeutic effects.We evaluated the impact of topoisomerase inhibitors in rAAV delivered endostatin gene therapy in a liver tumor model. METHODS:rAAV containing endostatin expression cassettes were transduced into hepatoma cell lines.To test whether the topoisomerase inhibitor pretreatment increased the expression of endostatin,Western blotting and ELISA were performed.The biologic activity of endostatin was confirmed by endothelial cell proliferation and tube formation assays. The anti-tumor effects of the rAAV-endostatin vector combined with a topoisomerase inhibitor,etoposide,were evaluated in a mouse liver tumor model. RESULTS:Topoisomerase inhibitors,including camptothecin and etoposide,were found to increase the endostatin exPression level in vitro.The over-expressed endostatin, as a result of pretreatment with a topoisomerase inhibitor, was also biologically active.In animal experiments,the combined therapy of topoisomerase inhibitor,etoposide with the rAAV-endostatin vector had the best tumor- suppressive effect and tumor foci were barely observed in livers of the treated mice.Pretreatment with an etoposide increased the level of endostatin in the liver and serum of rAAV-endostatin treated mice.Finally,the mice treated With rAAV-endostatin in combination with etoposide showed the longest survival among the experimental models. CONCLUSION:rAAV delivered endostatin gene therapy in combination with a topoisomerase inhibitor pretreatment is an effective modality for anticancer gene therapy.
文摘提出了一种基于最小二乘支持向量机的织物剪切性能预测模型,并且采用遗传算法进行最小二乘支持向量机的参数优化,将获得的样本进行归一化处理后,将其输入预测模型以得到预测结果.仿真结果表明,基于最小二乘支持向量机的预测模型比BP神经网络和线性回归方法具有更高的精度和范化能力.
Abstract：
A new method is proposed to predict the fabric shearing property with least square support vector machines ( LS-SVM ). The genetic algorithm is investigated to select the parameters of LS-SVM models as a means of improving the LS- SVM prediction. After normalizing the sampling data, the sampling data are inputted into the model to gain the prediction result. The simulation results show the prediction model gives better forecasting accuracy and generalization ability than BP neural network and linear regression method.
文摘The beneficial acclimation hypothesis (BAH) predicts that animals acclimated to a particular temperature have enhanced performance or fitness at that temperature in comparison with animals acclimated to other temperatures. The BAH has been tested by a variety of empirical examinations, and was rejected by some of them. In order to provide new evidences for the BAH, the effects of acute and acclimation temperature (AT) on locomotor performance of Macrobiotus hufelandi (Tardigrada: Macrobiotidae) were investigated. The tardigrades were collected from Nanwutai, Qinling Mountains which traverse from west to east in central China. The subjects were acclimated to either 2℃ or 22℃ for 2 weeks. The animal was transferred onto a frosted slide and allowed to walk freely at the performance temperature (PT) 2℃ or 22℃. Only one individual was tested per test bout, which lasted from three to five minutes. To avoid occurrence of thermal acclimation effect, the standard adaptation time was limited to 1.5 min. Each subject was tested for once at the same PT, and was tested only at one PT. A total of 25 individuals were tested and measured at the same PT. The locomotor performance of the animals was recorded with a digital video camera mounted on a microscope at 4×10 amplification and replayed on a PC. Every subject was identified. Walking speed (WS) and percentage of time moving (PTM) at both PTs (2℃ or 22℃) were selected as the rate parameters of locomotor performance. The two-way repeated measures ANOVA with a significance level of α= 0.05 and Duncan multiple range test were used to analyze the data. WS of the animals acclimated to and tested at the same temperatures was significantly faster than that for animals acclimated to and tested at the different temperatures, similarly, PTM of the animals acclimated to 22℃ and tested at 22℃ was significantly greater than PTM of animals acclimated to 22℃ and tested at 2℃, which indicated that the animals acclimated to a particular temperature have enhanced locomotor performance in that temperature relative to the animals acclimated to that temperature in other thermal environment. WS of the animals acclimated to 22℃ and tested at 22℃ was significantly faster than WS of animals acclimated to 2℃ and tested at 22℃, PTM of the animals acclimated to 22℃ and tested at 22℃ was significantly greater than PTM of animals acclimated to 2℃ and tested at 22℃. These results supported the BAH. It could be concluded that the PT and thermal acclimation as well as the interaction between the PT and AT significantly influence the locomotor performance of M.hufelandi, and that, despite the existence of a few results of this study that don’t support the BAH, some results of this study support for this hypothesis, and that the animals acclimated to a particular temperature have enhanced locomotor performance in that temperature relative to the animals acclimated to that temperature in other thermal environment, implying that any performance temperature that deviates from the acclimation temperature could cause the reduction of the walking speed which is closely related to the fitness of the M.hufelandi.
文摘The present pagination reports both Brownian diffusion and thermophoresis aspects subject to magneto hydrodynamic Williamson fluid model.Assuming the flow is unsteady and blood is treated as Williamson fluid over a wedge with radiation.The governing equations are transformed into ordinary differential equations by using similarity variables.The analytical solutions of the transformed governing equations are obtained by using the RK 4th order method along with shooting technique solver.The effects of various physical parameters such as Hartmann number,local Weissenberg number,radiation parameter,unsteadiness parameter,Prandtl number,Lewis number,Brownian diffusion,thermophoresis,wedge angle parameter,moving wedge parameter,on velocity,temperature,concentration,skin friction,heat transfer rate and mass transfer rate have been discussed in detail.The velocity and temperature profile deprives for larger We and an opposite trend is observed for concentration.The radiation parameter is propositional to temperature and a counter behaviour is observed for Pr.
文摘Switzerland is one of the most desirable European destinations for Chinese tourists;therefore, a better understanding of Chinese tourists is essential for successful business practices. In China, the largest and leading social media platform—Sina Weibo, a hybrid of Twitter and Facebook—has more than 600 million users. Weibo’s great market penetration suggests that tourism operators and markets need to understand how to build effective and sustainable communications on Chinese social media platforms. In order to offer a better decision support platform to tourism destination managers as well as Chinese tourists, we proposed a framework using linked data on Sina Weibo. Linked Data is a term referring to using the Internet to connect related data. We will show how it can be used and how ontology can be designed to include the users’ context (e.g., GPS locations). Our framework will provide a good theoretical foundation for further understand Chinese tourists’ expectation, experiences, behaviors and new trends in Switzerland.
基金The work described in this paper was fully supported by a grant from Hong Kong Metropolitan University(RIF/2021/05).
文摘Parkinson’s disease(PD)is a debilitating neurological disorder affecting over 10 million people worldwide.PD classification models using voice signals as input are common in the literature.It is believed that using deep learning algorithms further enhances performance;nevertheless,it is challenging due to the nature of small-scale and imbalanced PD datasets.This paper proposed a convolutional neural network-based deep support vector machine(CNN-DSVM)to automate the feature extraction process using CNN and extend the conventional SVM to a DSVM for better classification performance in small-scale PD datasets.A customized kernel function reduces the impact of biased classification towards the majority class(healthy candidates in our consideration).An improved generative adversarial network(IGAN)was designed to generate additional training data to enhance the model’s performance.For performance evaluation,the proposed algorithm achieves a sensitivity of 97.6%and a specificity of 97.3%.The performance comparison is evaluated from five perspectives,including comparisons with different data generation algorithms,feature extraction techniques,kernel functions,and existing works.Results reveal the effectiveness of the IGAN algorithm,which improves the sensitivity and specificity by 4.05%–4.72%and 4.96%–5.86%,respectively;and the effectiveness of the CNN-DSVM algorithm,which improves the sensitivity by 1.24%–57.4%and specificity by 1.04%–163%and reduces biased detection towards the majority class.The ablation experiments confirm the effectiveness of individual components.Two future research directions have also been suggested.
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Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.
基金This work was supported by the National Key R&D Program of China(Grant No.2018YFB1304902)the National Natural Science Foundation of China(Grant Nos.12004034,U1813211,22005247,11904372,51502007,52072323,52122211,12174019,and 51972058)+1 种基金the Gen-eral Research Fund of Hong Kong(Project No.11217221)China Postdoctoral Science Foundation Funded Project(Grant No.2021M690386).
文摘Potassium-ion batteries(PIBs)are considered promising alternatives to lithium-ion batteries owing to cost-effective potassium resources and a suitable redox potential of-2.93 V(vs.-3.04 V for Li+/Li).However,the exploration of appro-priate electrode materials with the correct size for reversibly accommodating large K+ions presents a significant challenge.In addition,the reaction mecha-nisms and origins of enhanced performance remain elusive.Here,tetragonal FeSe nanoflakes of different sizes are designed to serve as an anode for PIBs,and their live and atomic-scale potassiation/depotassiation mechanisms are revealed for the first time through in situ high-resolution transmission electron micros-copy.We found that FeSe undergoes two distinct structural evolutions,sequen-tially characterized by intercalation and conversion reactions,and the initial intercalation behavior is size-dependent.Apparent expansion induced by the intercalation of K+ions is observed in small-sized FeSe nanoflakes,whereas unexpected cracks are formed along the direction of ionic diffusion in large-sized nanoflakes.The significant stress generation and crack extension originating from the combined effect of mechanical and electrochemical interactions are elucidated by geometric phase analysis and finite-element analysis.Despite the different intercalation behaviors,the formed products of Fe and K_(2)Se after full potassiation can be converted back into the original FeSe phase upon depotassiation.In particular,small-sized nanoflakes exhibit better cycling perfor-mance with well-maintained structural integrity.This article presents the first successful demonstration of atomic-scale visualization that can reveal size-dependent potassiation dynamics.Moreover,it provides valuable guidelines for optimizing the dimensions of electrode materials for advanced PIBs.
基金Supported by Commissioned Project of Office of Rural Work Leading Group of Kunming Municipal Committee of the Communist Party of China"Study on the Poverty Alleviation Model of Kunming City in the Context of World Poverty Reduction"
文摘Poverty alleviation by supporting industry is a key measure to promote the poverty alleviation of relocated households. Taking Xundian County, the first county in Yunnan Province that has been lifted out of poverty, as an research case, this article analyzes and summarizes the industry-supporting poverty alleviation achievements and successful experience of two typical relocation areas (Shanhou Village and Eyang Village) in Xundian County. Practice has shown that the key to industry-supporting poverty alleviation lies in targetedness to strengthen the participation of poor farmers in industrial development. The interests of poverty alleviation entities should be linked by market mechanism to establish a benign interaction between all parties for win-win situation, thereby effectively guaranteeing the long-term and healthy development of poverty alleviation by supporting industry.
文摘Nowadays, power quality issues are becoming a significant research topic because of the increasing inclusion of very sensitive devices and considerable renewable energy sources. In general, most of the previous power quality classification techniques focused on single power quality events and did not include an optimal feature selection process. This paper presents a classification system that employs Wavelet Transform and the RMS profile to extract the main features of the measured waveforms containing either single or complex disturbances. A data mining process is designed to select the optimal set of features that better describes each disturbance present in the waveform. Support Vector Machine binary classifiers organized in a “One Vs Rest” architecture are individually optimized to classify single and complex disturbances. The parameters that rule the performance of each binary classifier are also individually adjusted using a grid search algorithm that helps them achieve optimal performance. This specialized process significantly improves the total classification accuracy. Several single and complex disturbances were simulated in order to train and test the algorithm. The results show that the classifier is capable of identifying >99% of single disturbances and >97% of complex disturbances.
文摘The seedlings of Vernicia montana derived from seeds soaking with water (the first group)or 300 mg5L -1 mixed nitric_acid rare earth solution (the second group) were treated with various concentrations of mixed nitric_acid rare earth solution by foliage spraying. The results showed that the seedling heights sprayed with 100 和 1 000 mg·L -1 of the first group and with 50 和 100 mg·L -1 of the second group were significantly higher than the controls, and the diameter at ground level sprayed with 300 mg·L -1 of the second group was significantly greater than the control, being 26.92% more than the latter; except for spraying with 0 mg5L -1 and 700～1 500 mg5L -1 of the second group, the seedling dry weight above ground of others was 29.13%～73.91% greater than the control, whereas the seedling dry weight under ground of others was 20.78%～116.88% greater than the control; the contents of chlorophyll a and chlorophyll b for all spraying seedling were 91.67%～191.67% and 87.5%～306.25% greater than the control, respectively, and soluble proteins and soluble sugars were 16.00%～179.78% and 10.73%～105.65% greater than the control, respectively. Compared with the control, the activity of SOD tended to increase, whereas the contents of MDA decreased. These indicated that spraying leaves with optimum concentration of mixed nitric_acid rare earth solution could markedly promote the growth of seedlings and improve resistance ability of V. montana seedlings to bad environment. On the whole, the effects of spraying the leaves of seedling with 50～500 mg5L -1 mixed nitric_acid rare earth solution, which were derived from seeds soaking with 300 mg·L -1 mixed nitric_acid rare earth solution, were good.
基金the National Natural Science Fund of China(Approved No.79779986)
文摘Intelligent Decision Support System (IISS) for Bank Loans Risk Classification (BLRC), based on the way of integration Artificial Neural Network (ANN) and Expert System (ES), is proposed. According to the feature of BLRC, the key financial and non-financial factors are analyzed. Meanwhile, ES and Model Base (MB) which contain ANN are designed . The general framework,interaction and integration of the system are given. In addition, how the system realizes BLRC is elucidated in detail.
文摘A new binuclear copper(Ⅱ) complex, [Cu2(phen)2(H2O)2( μ2-C2O4)](NO3)2, has been synthesized and characterized by elemental analysis, IR and UV-Vis spectrum. Its crystal structure was determined by single crystal X-ray diffraction techniques. Crystal data: monoclinic, space group P21/c, a=0.712 21(8) nm, b=1.170 93(14) nm, c=1.783 7(2) nm, β=111.828(2)°, and V=1.380 8(3) nm3, Dc=1.769 Mg·m-3, Z=2, F(000)=744, R1=0.025 4, wR2=0.069 5, Gof=1.077, Δρ=328^-455 e·nm-3. The complex is packed by one centrosymmetry binuclear copper(Ⅱ) unit, oxalate dianion and NO3- anion. In the molecule structure of the title complex, two Cu(Ⅱ) ions are bridged by oxalate dianion and each Cu(Ⅱ) ions coordinates with two nitrogen atoms from 1,10-phenanthroline ligand and one oxygen atom from water to form a five-coordinate distorted square-pyramidal configuration. The hydrogen bonds are observed between coordinated water molecules and NO3- anions. The analysis of the crystal structure indicates that the complex has a two-dimensional stacking network structure, which is formed by intramolecular hydrogen bonds, intermolecular hydrogen bonds and stacking effect of aromatic ring. CCDC: 255345.
文摘In this work, a total of 322 tests were taken on young volunteers by performing 10 different falls, 6 different Activities of Daily Living (ADL) and 7 Dynamic Gait Index (DGI) tests using a custom-designed Wireless Gait Analysis Sensor (WGAS). In order to perform automatic fall detection, we used Back Propagation Artificial Neural Network (BP-ANN) and Support Vector Machine (SVM) based on the 6 features extracted from the raw data. The WGAS, which includes a tri-axial accelerometer, 2 gyroscopes, and a MSP430 microcontroller, is worn by the subjects at either T4 (at back) or as a belt-clip in front of the waist during the various tests. The raw data is wirelessly transmitted from the WGAS to a near-by PC for real-time fall classification. The BP ANN is optimized by varying the training, testing and validation data sets and training the network with different learning schemes. SVM is optimized by using three different kernels and selecting the kernel for best classification rate. The overall accuracy of BP ANN is obtained as 98.20% with LM and RPROP training from the T4 data, while from the data taken at the belt, we achieved 98.70% with LM and SCG learning. The overall accuracy using SVM was 98.80% and 98.71% with RBF kernel from the T4 and belt position data, respectively.
