Common neurodegenerative diseases of the central nervous system are characterized by progressive damage to the function of neurons, even leading to the permanent loss of function. Gene therapy via gene replacement or ...Common neurodegenerative diseases of the central nervous system are characterized by progressive damage to the function of neurons, even leading to the permanent loss of function. Gene therapy via gene replacement or gene correction provides the potential for transformative therapies to delay or possibly stop further progression of the neurodegenerative disease in affected patients. Adeno-associated virus has been the vector of choice in recent clinical trials of therapies for neurodegenerative diseases due to its safety and efficiency in mediating gene transfer to the central nervous system. This review aims to discuss and summarize the progress and clinical applications of adeno-associated virus in neurodegenerative disease in central nervous system. Results from some clinical trials and successful cases of central neurodegenerative diseases deserve further study and exploration.展开更多
The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates ...The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.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
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
In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independentl...In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples.展开更多
It is shown that such phenomena as quantum correlations (interaction of space-separated quantum entities), the action of magnetic vector potential on quantum entities in the absence of magnetic field, and near-field a...It is shown that such phenomena as quantum correlations (interaction of space-separated quantum entities), the action of magnetic vector potential on quantum entities in the absence of magnetic field, and near-field antenna effect (the existence of superluminally propagating electromagnetic fields) may be explained by action of spin supercurrents. In case of quantum correlations between quantum entities, spin supercurrent emerges between virtual particles pairs (virtual photons) created by those quantum entities. The explanation of magnetic vector potential and near-field antenna effect is based on contemporary principle of quantum mechanics: the physical vacuum is not an empty space but the ground state of the field consisting of quantum harmonic oscillators (QHOs) characterized by zero-point energy. Using the properties of the oscillators and spin supercurrent, it is proved that magnetic vector potential is proportional to the moment causing the orientation of spin of QHO along the direction of magnetic field. The near-field antenna effect is supposed to take place as a result of action of spin supercurrent causing secondary electromagnetic oscillations. In this way, the electromagnetic field may spread at the speed of spin supercurrent. As spin supercurrent is an inertia free process, its speed may be greater than that of light, which does not contradict postulates of special relativity that sets limits to the speed of inertial systems only.展开更多
Objective:To evaluate the Anaplasma phagocytophilum(A.phagocytophilum),Ehrlichia canis(E.canis,Dirofilaria immitis(D.immitis)(canine heartworm),Borrelia burgdorferi(B.burgdorferi)infections in countryside dogs from Yu...Objective:To evaluate the Anaplasma phagocytophilum(A.phagocytophilum),Ehrlichia canis(E.canis,Dirofilaria immitis(D.immitis)(canine heartworm),Borrelia burgdorferi(B.burgdorferi)infections in countryside dogs from Yunnan,Hainan and Anhui provinces.Methods:Serum samples were collected from 26 dogs in Yunnan.Hainan and Anhui provinces.The samples were tested using a commercial ELISA rapid diagnostic assay kit(SNAP^(?)4Dx^(?);IDEXX Laboratories,Inc.U.S.A.).Meaiiwliile,indirect immunofluorescence assay(IFA)recommended by WHO was conducted to delect IgG to A.phagocytophilum.Two methods were analyzed and compared.Results:The number of serologically positive dogs for IgG to A.phagocytophilum was only 2which was from Hainan province and none of the 26 dogs responded positive for E.canu.D.immitis(canine heartworm,and B.burgdorferi by ELISA rapid diagnostic method.The number of serologically positive dogs for IgG to A.phagocytophilum was 13(50%)by IFA method.Data of the two methods were analyzed by statistical software and the difference was statistically significant(P=0.002).Conclusions:It can be concluded that IFA method was more sensitive than ELISA rapid diagnostic method.However,we need conduct further and intensive epidemiology survey on tick-born diseases pathogens including.4.phagocytophilum,E.canis,D.immitis(canine heartworm),and B.burgdorferi which have public health significance.展开更多
AIM: To kill CEA positive colorectal carcinoma cells specifically using the E coli cytosine deaminase (CD) suicide gene, a new replication-deficient recombinant adenoviral vector was constructed in which CD gene was c...AIM: To kill CEA positive colorectal carcinoma cells specifically using the E coli cytosine deaminase (CD) suicide gene, a new replication-deficient recombinant adenoviral vector was constructed in which CD gene was controlled under CEA promoter and its in vitro cytotoxic effects were evaluated. METHODS: Shuttle plasmid containing CD gene and regulatory sequence of the CEA gene was constructed and recombined with the right arm of adenovirus genome DNA in 293 cell strain. Dot blotting and PCR were used to identify positive plaques. The purification of adenovirus was performed with ultra-concentration in CsCl step gradients and the titration was measured with plaque formation assay. Cytotoxic effects were assayed with MTT method, The fifty percent inhibition concentration (IC(50)) of 5-FC was calculated using a curve-fitting parameter. The human colorectal carcinoma cell line, which was CEA-producing, and the CEA-nonproducing Hela cell line were applied in cytological tests. An established recombinant adenovirus vector AdCMVCD, in which the CD gene was controlled under CMV promoter, was used as virus control. Quantitative results were expressed as the mean +/- SD of the mean. Statistical analysis was performed using ANOVA test. RESULTS: The desired recombinant adenovirus vector was named AdCEACD. The results of dot blotting and PCR showed that the recombinant adenovirus contained CEA promoter and CD gene. Virus titer was about 5.0 X 10(14)pfu/L(-1) after purification. The CEA-producing Lovo cells were sensitive to 5-FC and had the same cytotoxic effect after infection with AdCEACD and AdCMVCD (The IC(50) values of 5-FC in parent Lovo cells, Lovo cells infected with 100 M.O.I AdCEACD and Lovo cells infected with 10 M.O.I AdCMVCD were 】15000, 216.5+/-38.1 and 128.8+/-25.4 micromol.L(-1), P【0.001, respectively), and the cytotoxicity of 5-FC increased accordingly when the m.o.i of adenoviruses were enhanced (The value of IC(50) of 5-FC was reduced to 27.9+/-4.2 micromol.L(-1) in 1000 M.O.I AdCEACD infected Lovo cells and 24.8+/-7.1 micromol.L(-1) in 100 M.O.I AdCMVCD infected Lovo cells, P【0.05, P【0.01, respectively). The CEA-nonproducing Hela cells had no effect after infection with AdCEACD, but Hela cells had the cytotoxic sensitivity to 5-FC after infection with AdCMVCD (The IC(50) of 5-FC in parent Hele cells and Hela cells infected with AdCMVCD at 10 M.O.I was 】15000 and 214.5+/-31.3 micromol.L(-1), P【0.001). AdCEACD/5-FC system also had bystander effect, and the viability was about 30 percent when the proportion of transfected cells was only 10 percent. CONCLUSION: The recombinant adenovirus vector AdCEACD has the character of cell type-specific gene delivery. The AdCEACD/5-FC system may become a new, potent and specific approach for the gene therapy of CEA-positive neoplasms, especially colon carcinoma.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
Objective:To evaluate the larvicidal and pupicidal potential of the methanolic extracts from Moringa oleifera(M.oleifera) plant seeds against malarial vector Anopheles stephensi(A.stephensi) mosquitoes at different co...Objective:To evaluate the larvicidal and pupicidal potential of the methanolic extracts from Moringa oleifera(M.oleifera) plant seeds against malarial vector Anopheles stephensi(A.stephensi) mosquitoes at different concentrations(20,40,60,80 and 100 ppm).Methods:M.oleifera was collected from the area of around Bharathiar University,Coimbatore.The dried plant materials were powdered by an electrical blender.From each sample,100 g of the plant material were extracted with 300 mL of methanol for 8 h in a Soxhlet apparatus.The extracts were evaporated to dryness in rotary vacuum evaporator to yield 122 mg and 110 mg of dark greenish material(residue) from Arcang amara and Ocimum basilicum,respectively.One gram of the each plant residue was dissolved separately in 100 mL of acetone(stock solution) from which different concentrations, i.e.,20,40,60,80 and 100 ppm were prepared.Results:Larvicidal activity of M.oleifera exhibited in the first to fourth instar larvae of the A.stephensi,and the LC_(50) and LC_(90) values were 57.79 ppm and 125.93 ppm for the first instar,63.90 ppm and 133.07 ppm for the second inslar,72.45 ppm and 139.82 ppm for the third instar,78.93 ppm and 143.20 ppm for the fourth instar,respectively. During the pupal stage the methanolic extract of M.oleifera showed that the LC_(50),and LC_(90) values were 67.77 ppm and 141.00 ppm,respectively.Conclusions:The present study indicates that the phytochemicals derived from M.oleifera seeds extracts are effective mosquito vector control agents and the plant extracts may be used for further integrated pest management programs.展开更多
In this paper, we introduce and study the system of generalized vector quasi-variational-like inequalities in Hausdorff topological vector spaces, which include the system of vector quasi-variational-like inequalities...In this paper, we introduce and study the system of generalized vector quasi-variational-like inequalities in Hausdorff topological vector spaces, which include the system of vector quasi-variational-like inequalities, the system of vector variational-like inequalities, the system of vector quasi-variational inequalities, and several other systems as special cases. Moreover, a number of C-diagonal quasiconvexity properties are proposed for set-valued maps, which are natural generalizations of the g-diagonal quasiconvexity for real functions. Together with an application of continuous selection and fixed-point theorems, these conditions enable us to prove unified existence results of solutions for the system of generalized vector quasi-variational-like inequalities. The results of this paper can be seen as extensions and generalizations of several known results in the literature.展开更多
Based on the research of predictingβ-hairpin motifs in proteins, we apply Random Forest and Support Vector Machine algorithm to predictβ-hairpin motifs in ArchDB40 dataset. The motifs with the loop length of 2 to 8 ...Based on the research of predictingβ-hairpin motifs in proteins, we apply Random Forest and Support Vector Machine algorithm to predictβ-hairpin motifs in ArchDB40 dataset. The motifs with the loop length of 2 to 8 amino acid residues are extracted as research object and thefixed-length pattern of 12 amino acids are selected. When using the same characteristic parameters and the same test method, Random Forest algorithm is more effective than Support Vector Machine. In addition, because of Random Forest algorithm doesn’t produce overfitting phenomenon while the dimension of characteristic parameters is higher, we use Random Forest based on higher dimension characteristic parameters to predictβ-hairpin motifs. The better prediction results are obtained;the overall accuracy and Matthew’s correlation coefficient of 5-fold cross-validation achieve 83.3% and 0.59, respectively.展开更多
Many animals possess actively movable tactile sensors in their heads,to explore the near-range space.During locomotion,an antenna is used in near range orientation,for example,in detecting,localizing,probing,and negot...Many animals possess actively movable tactile sensors in their heads,to explore the near-range space.During locomotion,an antenna is used in near range orientation,for example,in detecting,localizing,probing,and negotiating obstacles.A bionic tactile sensor used in the present work was inspired by the antenna of the stick insects.The sensor is able to detect an obstacle and its location in 3 D(Three dimensional) space.The vibration signals are analyzed in the frequency domain using Fast Fourier Transform(FFT) to estimate the distances.Signal processing algorithms,Artificial Neural Network(ANN) and Support Vector Machine(SVM) are used for the analysis and prediction processes.These three prediction techniques are compared for both distance estimation and material classification processes.When estimating the distances,the accuracy of estimation is deteriorated towards the tip of the probe due to the change in the vibration modes.Since the vibration data within that region have high a variance,the accuracy in distance estimation and material classification are lower towards the tip.The change in vibration mode is mathematically analyzed and a solution is proposed to estimate the distance along the full range of the probe.展开更多
Objective:To assess the larvicidal and irritant activities of the hexane extracts of leaves of Citrus sinensis(C.sinensis)against the early fourth instars and female adults of Aedes aegypti(Ae.aegypti).Methods:The lar...Objective:To assess the larvicidal and irritant activities of the hexane extracts of leaves of Citrus sinensis(C.sinensis)against the early fourth instars and female adults of Aedes aegypti(Ae.aegypti).Methods:The larvicidal potential of the prepared leaf extract was evaluated against early fourth instar larvae of Ae.aegypli using WHO protocol.The mortality counts were made after 24 h and LC_(50)and LG_(50)values were calculated.The efficacy of extract as mosquito irritant was assessed by contact irritancy assays.Extract-impregnated paper was placed on a glass plate over which a perspex funnel with a hole on the top was kept inverted.Single female adult,3-day old unfed/blood-fed,was released inside the funnel.After 3 min of acclimatization time,the time taken for the first take-off and total number of flights undertaken during 15 min were scored.Results:The citrus leaf extracts from hexane possessed moderate larvicidal efficiency against dengue vector.The bioassays resulted in an LC_(50)and LC_(90)value of 446.84 and 1370.96 ppm,respectively after 24 h of exposure.However,the extracts were proved to be remarkable irritant against adults Ae.aegypti,more pronounced effects being observed on blood-fed females than unfed females.The extract-impregnated paper was thus proved to be 7-11 times more irritable as compared with the control paper.Conclusions:The hexane extracts from C.sinensis leaves are proved to be reasonably larvicidal But remarkably irritant against dengue vector.Further studies are needed to identify the possible role of extract as adulticide,oviposition deterrent and ovicidal agent.The isolation of active ingredient from the extract could help in formulating strategies for mosquito control.展开更多
As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a mult...As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a multi-step model predictive control based on online SVR(OSVR) optimized by multi-agent particle swarm optimization algorithm(MAPSO) is put forward. By integrating the online learning ability of OSVR, the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well.展开更多
The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to ov...The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.展开更多
One of the classical approaches in the analysis of a variational inequality problem is to transform it into an equivalent optimization problem via the notion of gap function. The gap functions are useful tools in deri...One of the classical approaches in the analysis of a variational inequality problem is to transform it into an equivalent optimization problem via the notion of gap function. The gap functions are useful tools in deriving the error bounds which provide an estimated distance between a specific point and the exact solution of variational inequality problem. In this paper, we follow a similar approach for set-valued vector quasi variational inequality problems and define the gap functions based on scalarization scheme as well as the one with no scalar parameter. The error bounds results are obtained under fixed point symmetric and locally α-Holder assumptions on the set-valued map describing the domain of solution space of a set-valued vector quasi variational inequality problem.展开更多
In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying result...In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.展开更多
Machine learning method has been widely used in various geotechnical engineering risk analysis in recent years. However, the overfitting problem often occurs due to the small number of samples obtained in history. Thi...Machine learning method has been widely used in various geotechnical engineering risk analysis in recent years. However, the overfitting problem often occurs due to the small number of samples obtained in history. This paper proposes the FuzzySVM(support vector machine) geotechnical engineering risk analysis method based on the Bayesian network. The proposed method utilizes the fuzzy set theory to build a Bayesian network to reflect prior knowledge, and utilizes the SVM to build a Bayesian network to reflect historical samples. Then a Bayesian network for evaluation is built in Bayesian estimation method by combining prior knowledge with historical samples. Taking seismic damage evaluation of slopes as an example, the steps of the method are stated in detail. The proposed method is used to evaluate the seismic damage of 96 slopes along roads in the area affected by the Wenchuan earthquake. The evaluation results show that the method can solve the overfitting problem, which often occurs if the machine learning methods are used to evaluate risk of geotechnical engineering, and the performance of the method is much better than that of the previous machine learning methods. Moreover,the proposed method can also effectively evaluate various geotechnical engineering risks in the absence of some influencing factors.展开更多
In this paper.we discuss Lagrangian vector field on Kahler manifold and use it to describe and solve some problem in Newtonican and Lagrangian Mechanics on Kahler Manifold.
文摘Common neurodegenerative diseases of the central nervous system are characterized by progressive damage to the function of neurons, even leading to the permanent loss of function. Gene therapy via gene replacement or gene correction provides the potential for transformative therapies to delay or possibly stop further progression of the neurodegenerative disease in affected patients. Adeno-associated virus has been the vector of choice in recent clinical trials of therapies for neurodegenerative diseases due to its safety and efficiency in mediating gene transfer to the central nervous system. This review aims to discuss and summarize the progress and clinical applications of adeno-associated virus in neurodegenerative disease in central nervous system. Results from some clinical trials and successful cases of central neurodegenerative diseases deserve further study and exploration.
基金supported by grants PID2020-120308RB-I00 and PID2023-147802OB-I00 funded by MICIU/AEI/10.13039/501100011033FEDER,UE,by Aligning Science Across Parkinson’s(ref.ASAP-020505)through the Michael J.Fox Foundation for Parkinson’s Research+1 种基金by CiberNed Intramural Collaborative Projects(ref.PI2020/09)by the Spanish Fundación Mutua Madrile?a de Investigación Médica(to JLL)。
文摘The development of clinical candidates that modify the natural progression of sporadic Parkinson's disease and related synucleinopathies is a praiseworthy endeavor,but extremely challenging.Therapeutic candidates that were successful in preclinical Parkinson's disease animal models have repeatedly failed when tested in clinical trials.While these failures have many possible explanations,it is perhaps time to recognize that the problem lies with the animal models rather than the putative candidate.In other words,the lack of adequate animal models of Parkinson's disease currently represents the main barrier to preclinical identification of potential disease-modifying therapies likely to succeed in clinical trials.However,this barrier may be overcome by the recent introduction of novel generations of viral vectors coding for different forms of alpha-synuclein species and related genes.Although still facing several limitations,these models have managed to mimic the known neuropathological hallmarks of Parkinson's disease with unprecedented accuracy,delineating a more optimistic scenario for the near future.
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In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples.
文摘It is shown that such phenomena as quantum correlations (interaction of space-separated quantum entities), the action of magnetic vector potential on quantum entities in the absence of magnetic field, and near-field antenna effect (the existence of superluminally propagating electromagnetic fields) may be explained by action of spin supercurrents. In case of quantum correlations between quantum entities, spin supercurrent emerges between virtual particles pairs (virtual photons) created by those quantum entities. The explanation of magnetic vector potential and near-field antenna effect is based on contemporary principle of quantum mechanics: the physical vacuum is not an empty space but the ground state of the field consisting of quantum harmonic oscillators (QHOs) characterized by zero-point energy. Using the properties of the oscillators and spin supercurrent, it is proved that magnetic vector potential is proportional to the moment causing the orientation of spin of QHO along the direction of magnetic field. The near-field antenna effect is supposed to take place as a result of action of spin supercurrent causing secondary electromagnetic oscillations. In this way, the electromagnetic field may spread at the speed of spin supercurrent. As spin supercurrent is an inertia free process, its speed may be greater than that of light, which does not contradict postulates of special relativity that sets limits to the speed of inertial systems only.
基金supported by the National Basic Research Program of China(973 Program)2010CB530200(2010CB530206)the China-US Collaborative Program on Emerging and Re-emerging Infectious Disease(No.1U2GGH000018-01)
文摘Objective:To evaluate the Anaplasma phagocytophilum(A.phagocytophilum),Ehrlichia canis(E.canis,Dirofilaria immitis(D.immitis)(canine heartworm),Borrelia burgdorferi(B.burgdorferi)infections in countryside dogs from Yunnan,Hainan and Anhui provinces.Methods:Serum samples were collected from 26 dogs in Yunnan.Hainan and Anhui provinces.The samples were tested using a commercial ELISA rapid diagnostic assay kit(SNAP^(?)4Dx^(?);IDEXX Laboratories,Inc.U.S.A.).Meaiiwliile,indirect immunofluorescence assay(IFA)recommended by WHO was conducted to delect IgG to A.phagocytophilum.Two methods were analyzed and compared.Results:The number of serologically positive dogs for IgG to A.phagocytophilum was only 2which was from Hainan province and none of the 26 dogs responded positive for E.canu.D.immitis(canine heartworm,and B.burgdorferi by ELISA rapid diagnostic method.The number of serologically positive dogs for IgG to A.phagocytophilum was 13(50%)by IFA method.Data of the two methods were analyzed by statistical software and the difference was statistically significant(P=0.002).Conclusions:It can be concluded that IFA method was more sensitive than ELISA rapid diagnostic method.However,we need conduct further and intensive epidemiology survey on tick-born diseases pathogens including.4.phagocytophilum,E.canis,D.immitis(canine heartworm),and B.burgdorferi which have public health significance.
基金the Creation Foundation of Nanjing Medical University,No.Cx9905
文摘AIM: To kill CEA positive colorectal carcinoma cells specifically using the E coli cytosine deaminase (CD) suicide gene, a new replication-deficient recombinant adenoviral vector was constructed in which CD gene was controlled under CEA promoter and its in vitro cytotoxic effects were evaluated. METHODS: Shuttle plasmid containing CD gene and regulatory sequence of the CEA gene was constructed and recombined with the right arm of adenovirus genome DNA in 293 cell strain. Dot blotting and PCR were used to identify positive plaques. The purification of adenovirus was performed with ultra-concentration in CsCl step gradients and the titration was measured with plaque formation assay. Cytotoxic effects were assayed with MTT method, The fifty percent inhibition concentration (IC(50)) of 5-FC was calculated using a curve-fitting parameter. The human colorectal carcinoma cell line, which was CEA-producing, and the CEA-nonproducing Hela cell line were applied in cytological tests. An established recombinant adenovirus vector AdCMVCD, in which the CD gene was controlled under CMV promoter, was used as virus control. Quantitative results were expressed as the mean +/- SD of the mean. Statistical analysis was performed using ANOVA test. RESULTS: The desired recombinant adenovirus vector was named AdCEACD. The results of dot blotting and PCR showed that the recombinant adenovirus contained CEA promoter and CD gene. Virus titer was about 5.0 X 10(14)pfu/L(-1) after purification. The CEA-producing Lovo cells were sensitive to 5-FC and had the same cytotoxic effect after infection with AdCEACD and AdCMVCD (The IC(50) values of 5-FC in parent Lovo cells, Lovo cells infected with 100 M.O.I AdCEACD and Lovo cells infected with 10 M.O.I AdCMVCD were 】15000, 216.5+/-38.1 and 128.8+/-25.4 micromol.L(-1), P【0.001, respectively), and the cytotoxicity of 5-FC increased accordingly when the m.o.i of adenoviruses were enhanced (The value of IC(50) of 5-FC was reduced to 27.9+/-4.2 micromol.L(-1) in 1000 M.O.I AdCEACD infected Lovo cells and 24.8+/-7.1 micromol.L(-1) in 100 M.O.I AdCMVCD infected Lovo cells, P【0.05, P【0.01, respectively). The CEA-nonproducing Hela cells had no effect after infection with AdCEACD, but Hela cells had the cytotoxic sensitivity to 5-FC after infection with AdCMVCD (The IC(50) of 5-FC in parent Hele cells and Hela cells infected with AdCMVCD at 10 M.O.I was 】15000 and 214.5+/-31.3 micromol.L(-1), P【0.001). AdCEACD/5-FC system also had bystander effect, and the viability was about 30 percent when the proportion of transfected cells was only 10 percent. CONCLUSION: The recombinant adenovirus vector AdCEACD has the character of cell type-specific gene delivery. The AdCEACD/5-FC system may become a new, potent and specific approach for the gene therapy of CEA-positive neoplasms, especially colon carcinoma.
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.
文摘Objective:To evaluate the larvicidal and pupicidal potential of the methanolic extracts from Moringa oleifera(M.oleifera) plant seeds against malarial vector Anopheles stephensi(A.stephensi) mosquitoes at different concentrations(20,40,60,80 and 100 ppm).Methods:M.oleifera was collected from the area of around Bharathiar University,Coimbatore.The dried plant materials were powdered by an electrical blender.From each sample,100 g of the plant material were extracted with 300 mL of methanol for 8 h in a Soxhlet apparatus.The extracts were evaporated to dryness in rotary vacuum evaporator to yield 122 mg and 110 mg of dark greenish material(residue) from Arcang amara and Ocimum basilicum,respectively.One gram of the each plant residue was dissolved separately in 100 mL of acetone(stock solution) from which different concentrations, i.e.,20,40,60,80 and 100 ppm were prepared.Results:Larvicidal activity of M.oleifera exhibited in the first to fourth instar larvae of the A.stephensi,and the LC_(50) and LC_(90) values were 57.79 ppm and 125.93 ppm for the first instar,63.90 ppm and 133.07 ppm for the second inslar,72.45 ppm and 139.82 ppm for the third instar,78.93 ppm and 143.20 ppm for the fourth instar,respectively. During the pupal stage the methanolic extract of M.oleifera showed that the LC_(50),and LC_(90) values were 67.77 ppm and 141.00 ppm,respectively.Conclusions:The present study indicates that the phytochemicals derived from M.oleifera seeds extracts are effective mosquito vector control agents and the plant extracts may be used for further integrated pest management programs.
文摘In this paper, we introduce and study the system of generalized vector quasi-variational-like inequalities in Hausdorff topological vector spaces, which include the system of vector quasi-variational-like inequalities, the system of vector variational-like inequalities, the system of vector quasi-variational inequalities, and several other systems as special cases. Moreover, a number of C-diagonal quasiconvexity properties are proposed for set-valued maps, which are natural generalizations of the g-diagonal quasiconvexity for real functions. Together with an application of continuous selection and fixed-point theorems, these conditions enable us to prove unified existence results of solutions for the system of generalized vector quasi-variational-like inequalities. The results of this paper can be seen as extensions and generalizations of several known results in the literature.
文摘Based on the research of predictingβ-hairpin motifs in proteins, we apply Random Forest and Support Vector Machine algorithm to predictβ-hairpin motifs in ArchDB40 dataset. The motifs with the loop length of 2 to 8 amino acid residues are extracted as research object and thefixed-length pattern of 12 amino acids are selected. When using the same characteristic parameters and the same test method, Random Forest algorithm is more effective than Support Vector Machine. In addition, because of Random Forest algorithm doesn’t produce overfitting phenomenon while the dimension of characteristic parameters is higher, we use Random Forest based on higher dimension characteristic parameters to predictβ-hairpin motifs. The better prediction results are obtained;the overall accuracy and Matthew’s correlation coefficient of 5-fold cross-validation achieve 83.3% and 0.59, respectively.
文摘Many animals possess actively movable tactile sensors in their heads,to explore the near-range space.During locomotion,an antenna is used in near range orientation,for example,in detecting,localizing,probing,and negotiating obstacles.A bionic tactile sensor used in the present work was inspired by the antenna of the stick insects.The sensor is able to detect an obstacle and its location in 3 D(Three dimensional) space.The vibration signals are analyzed in the frequency domain using Fast Fourier Transform(FFT) to estimate the distances.Signal processing algorithms,Artificial Neural Network(ANN) and Support Vector Machine(SVM) are used for the analysis and prediction processes.These three prediction techniques are compared for both distance estimation and material classification processes.When estimating the distances,the accuracy of estimation is deteriorated towards the tip of the probe due to the change in the vibration modes.Since the vibration data within that region have high a variance,the accuracy in distance estimation and material classification are lower towards the tip.The change in vibration mode is mathematically analyzed and a solution is proposed to estimate the distance along the full range of the probe.
基金supported by University Grants Commission[grant No.F.35-74/2009(SR)]
文摘Objective:To assess the larvicidal and irritant activities of the hexane extracts of leaves of Citrus sinensis(C.sinensis)against the early fourth instars and female adults of Aedes aegypti(Ae.aegypti).Methods:The larvicidal potential of the prepared leaf extract was evaluated against early fourth instar larvae of Ae.aegypli using WHO protocol.The mortality counts were made after 24 h and LC_(50)and LG_(50)values were calculated.The efficacy of extract as mosquito irritant was assessed by contact irritancy assays.Extract-impregnated paper was placed on a glass plate over which a perspex funnel with a hole on the top was kept inverted.Single female adult,3-day old unfed/blood-fed,was released inside the funnel.After 3 min of acclimatization time,the time taken for the first take-off and total number of flights undertaken during 15 min were scored.Results:The citrus leaf extracts from hexane possessed moderate larvicidal efficiency against dengue vector.The bioassays resulted in an LC_(50)and LC_(90)value of 446.84 and 1370.96 ppm,respectively after 24 h of exposure.However,the extracts were proved to be remarkable irritant against adults Ae.aegypti,more pronounced effects being observed on blood-fed females than unfed females.The extract-impregnated paper was thus proved to be 7-11 times more irritable as compared with the control paper.Conclusions:The hexane extracts from C.sinensis leaves are proved to be reasonably larvicidal But remarkably irritant against dengue vector.Further studies are needed to identify the possible role of extract as adulticide,oviposition deterrent and ovicidal agent.The isolation of active ingredient from the extract could help in formulating strategies for mosquito control.
基金the National Natural Science Foundation of China(No.60905066)the Natural Science Foundation of Chongqing(No.cstc2018jcyjA0667)
文摘As optimization of parameters affects prediction accuracy and generalization ability of support vector regression(SVR) greatly and the predictive model often mismatches nonlinear system model predictive control,a multi-step model predictive control based on online SVR(OSVR) optimized by multi-agent particle swarm optimization algorithm(MAPSO) is put forward. By integrating the online learning ability of OSVR, the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well.
基金Supported by the National Natural Science Foundation of China(20676013,61240047)
文摘The approaches to discrete approximation of Pareto front using multi-objective evolutionary algorithms have the problems of heavy computation burden, long running time and missing Pareto optimal points. In order to overcome these problems, an approach to continuous approximation of Pareto front using geometric support vector regression is presented. The regression model of the small size approximate discrete Pareto front is constructed by geometric support vector regression modeling and is described as the approximate continuous Pareto front. In the process of geometric support vector regression modeling, considering the distribution characteristic of Pareto optimal points, the separable augmented training sample sets are constructed by shifting original training sample points along multiple coordinated axes. Besides, an interactive decision-making(DM)procedure, in which the continuous approximation of Pareto front and decision-making is performed interactively, is designed for improving the accuracy of the preferred Pareto optimal point. The correctness of the continuous approximation of Pareto front is demonstrated with a typical multi-objective optimization problem. In addition,combined with the interactive decision-making procedure, the continuous approximation of Pareto front is applied in the multi-objective optimization for an industrial fed-batch yeast fermentation process. The experimental results show that the generated approximate continuous Pareto front has good accuracy and completeness. Compared with the multi-objective evolutionary algorithm with large size population, a more accurate preferred Pareto optimal point can be obtained from the approximate continuous Pareto front with less computation and shorter running time. The operation strategy corresponding to the final preferred Pareto optimal point generated by the interactive DM procedure can improve the production indexes of the fermentation process effectively.
文摘One of the classical approaches in the analysis of a variational inequality problem is to transform it into an equivalent optimization problem via the notion of gap function. The gap functions are useful tools in deriving the error bounds which provide an estimated distance between a specific point and the exact solution of variational inequality problem. In this paper, we follow a similar approach for set-valued vector quasi variational inequality problems and define the gap functions based on scalarization scheme as well as the one with no scalar parameter. The error bounds results are obtained under fixed point symmetric and locally α-Holder assumptions on the set-valued map describing the domain of solution space of a set-valued vector quasi variational inequality problem.
基金Project supported by the National Basic Research Program (973) of China (No. 2002CB312200) and the Center for Bioinformatics Pro-gram Grant of Harvard Center of Neurodegeneration and Repair,Harvard Medical School, Harvard University, Boston, USA
文摘In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes.
基金supported by the National Key Research and Development Program (Grant No. 2017YFC0504901)Sichuan Traffic Construction Science and Technology Project(Grant No. 2016B2–2)Doctoral Innovation Fund Program of Southwest Jiaotong University(Grant No. D-CX201804)
文摘Machine learning method has been widely used in various geotechnical engineering risk analysis in recent years. However, the overfitting problem often occurs due to the small number of samples obtained in history. This paper proposes the FuzzySVM(support vector machine) geotechnical engineering risk analysis method based on the Bayesian network. The proposed method utilizes the fuzzy set theory to build a Bayesian network to reflect prior knowledge, and utilizes the SVM to build a Bayesian network to reflect historical samples. Then a Bayesian network for evaluation is built in Bayesian estimation method by combining prior knowledge with historical samples. Taking seismic damage evaluation of slopes as an example, the steps of the method are stated in detail. The proposed method is used to evaluate the seismic damage of 96 slopes along roads in the area affected by the Wenchuan earthquake. The evaluation results show that the method can solve the overfitting problem, which often occurs if the machine learning methods are used to evaluate risk of geotechnical engineering, and the performance of the method is much better than that of the previous machine learning methods. Moreover,the proposed method can also effectively evaluate various geotechnical engineering risks in the absence of some influencing factors.
文摘In this paper.we discuss Lagrangian vector field on Kahler manifold and use it to describe and solve some problem in Newtonican and Lagrangian Mechanics on Kahler Manifold.
