Background： Most eukaryotic protein-coding genes exhibit alternative cleavage and polyadenylation （APA）, resulting in mRNA isoforms with different 3＇ untranslated regions （3＇ UTRs）. Studies have shown that brai...Background： Most eukaryotic protein-coding genes exhibit alternative cleavage and polyadenylation （APA）, resulting in mRNA isoforms with different 3＇ untranslated regions （3＇ UTRs）. Studies have shown that brain cells tend to express long 3＇ UTR isoforms using distal cleavage and polyadenylation sites （PASs）. Methods： Using our recently developed, comprehensive PAS database PolyA_DB, we developed an efficient method to examine APA, named Significance Analysis of Alternative Polyadenylation using RNA-seq （SAAP-RS）. We applied this method to study APA in brain cells and neurogenesis. Results： We found that neurons globally express longer 3＇ UTRs than other cell types in brain, and microglia and endothelial cells express substantially shorter 3＇ UTRs. We show that the 3＇ UTR diversity across brain cells can be corroborated with single cell sequencing data. Further analysis of APA regulation of 3＇ UTRs during differentiation of embryonic stem cells into neurons indicates that a large fraction of the APA events regulated in neurogenesis are similarly modulated in myogenesis, but to a much greater extent. Conclusion： Together, our data delineate APA profiles in different brain cells and indicate that APA regulation in neurogenesis is largely an augmented process taking place in other types of cell differentiation.展开更多
Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal op...Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal optimization(COO)for remanufacturing planning.The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model(HRFM).Numerical testing shows that our method is efficient and effective for selecting good plans with high probability.It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.展开更多
This study attempted to accurately segment the mammographic masses and distinguish malignant from benign tumors.An adaptive region growing algorithm with hybrid assessment function combined with maximum likelihood ana...This study attempted to accurately segment the mammographic masses and distinguish malignant from benign tumors.An adaptive region growing algorithm with hybrid assessment function combined with maximum likelihood analysis and maximum gradient analysis was developed in this paper.In order to accommodate different situations of masses,the likelihood and the edge gradients of segmented masses were weighted adaptively by the use of information entropy.106 benign and 110 malignant tumors were included in this study.We found that the proposed algorithm obtained segmentation contour more accurately and delineated the tumor body as well as tumor peripheral regions covering typical mass boundaries and some spiculation patterns.Then the segmented results were evaluated by the classification accuracy.42 features including age,intensity,shape and texture were extracted from each segmented mass and support vector machine(SVM)was used as a classifier.The classification accuracy was evaluated using the area(A_(z))under the receiver operating characteristic(ROC)curve.It was found that the maximum likelihood analysis achieved an A_(z)value of 0.835,the maximum gradient analysis got an A_(z)value of 0.932 and the hybrid assessment function performed the best classification result where the value of A_(z)was 0.948.In addition,compared with traditional region growing algorithm,our proposed algorithm is more adaptive and provides a better performance for future works.展开更多
Ultra-shallow Si p^(+)n junctions formed by plasma doping are characterized by electrochemical capacitance-voltage(ECV).By comparing ECV results with those of secondary ion mass spectroscopy(SIMS),it is found that the...Ultra-shallow Si p^(+)n junctions formed by plasma doping are characterized by electrochemical capacitance-voltage(ECV).By comparing ECV results with those of secondary ion mass spectroscopy(SIMS),it is found that the dopant concentration profiles in heavily-doped p+layer as well as junction depths measured by ECV are in good agreement with those measured by SIMS.However,the ECV measurement of dopant concentration in the underlying lightly doped n-type substrate is significantly influenced by the upper heavily-doped layer.The ECV technique is also easy to control and reproduce.The ECV results of ultra-shallow junctions(USJ)formed by plasma doping followed by different annealing processes show that ECV is capable of reliably characterizing a Si USJ with junction depth as low as 10 nm,and dopant concentration up to 10^(21) cm^(-3).Also,its depth resolution can be as fine as 1 nm.Therefore,it shows great potential in application for characterizing USJ in the sub-65 nm technology node CMOS devices.展开更多
An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method.Based on the Riccati equa-tion and optimal fusion rule weighted by scalars for state...An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method.Based on the Riccati equa-tion and optimal fusion rule weighted by scalars for state components,a self-tuning component decoupled informa-tion fusion Kalman filter is presented.It is proved that the filter converges to the optimal fusion Kalman filter in a realization by dynamic error system analysis method,so that it has asymptotic optimality.Its effectiveness is demon-strated by simulation for a tracking system with 3 sensors.展开更多
Background： Sequence-specific binding by transcription factors （TFs） plays a significant role in the selection and regulation of target genes. At the protein：DNA interface, amino acid side-chains construct a diver...Background： Sequence-specific binding by transcription factors （TFs） plays a significant role in the selection and regulation of target genes. At the protein：DNA interface, amino acid side-chains construct a diverse physicochemical network of specific and non-specific interactions, and seemingly subtle changes in amino acid identity at certain positions may dramatically impact TF：DNA binding. Variation of these specificity-determining residues （SDRs） is a major mechanism of functional divergence between TFs with strong structural or sequence homology. Methods： In this study, we employed a combination of high-throughput specificity profiling by SELEX and Spec-seq, structural modeling, and evolutionary analysis to probe the binding preferences of winged helix-turn-helix TFs belonging to the OmpR sub-family in Escherichia coil Results： We found that E. coli OmpR paralogs recognize tandem, variably spaced repeats composed of＂GT-A＂ or ＂GCT＂-containing half-sites. Some divergent sequence preferences observed within the ＂GT-A＂ mode correlate with amino acid similarity; conversely, ＂GCT＂-based motifs were observed for a subset of paralogs with low sequence homology. Direct specificity profiling of a subset of OmpR homologues （CpxR, RstA, and OmpR） as well as predicted ＂SDR-swap＂ variants revealed that individual SDRs may impact sequence preferences locally through direct contact with DNA bases or distally via the DNA backbone. Conclusions： Overall, our work provides evidence for a common structural code for sequence-specific wHTH：DNA interactions, and demonstrates that surprisingly modest residue changes can enable recognition of highly divergent sequence motifs. Further examination of SDR predictions will likely reveal additional mechanisms controlling the evolutionary divergence of this important class of transcriptional regulators.展开更多
Much of our current knowledge of biology has been constructed based on population-average measurements. However, advances in single-cell analysis have demonstrated the omnipresent nature of cell-to-cell variability in...Much of our current knowledge of biology has been constructed based on population-average measurements. However, advances in single-cell analysis have demonstrated the omnipresent nature of cell-to-cell variability in any population. On one hand, tremendous efforts have been made to examine how such variability arises, how it is regulated by cellular networks, and how it can affect cell-fate decisions by single cells. On the other hand, recent studies suggest that the variability may carry valuable information that can facilitate the elucidation of underlying regulatory networks or the classification of cell states. To this end, a major challenge is determining what aspects of variability bear significant biological meaning. Addressing this challenge requires the development of new computational tools, in conjunction with appropriately chosen experimental platforms, to more effectively describe and interpret data on cell- cell variability. Here, we discuss examples of when population heterogeneity plays critical roles in determining biologically and clinically significant phenotypes, how it serves as a rich information source of regulatory mechanisms, and how we can extract such information to gain a deeper understanding of biological systems.展开更多
Designing reliability differentiated services for missions with different reliability requirements has become a hot topic in wireless sensor networks.Combined with a location-based routing mechanism,a quantified model...Designing reliability differentiated services for missions with different reliability requirements has become a hot topic in wireless sensor networks.Combined with a location-based routing mechanism,a quantified model without full network topology is proposed to evaluate reliability.By introducing a virtual reference point,the data transfer is limited in a specified area.The reliability function of the area is given.A detailed analysis shows that the function increases quadratically with the distance between the source node and the reference node.A reliability differentiated service mechanism is then proposed.The simulation results show the efficiency of the proposed mechanism.展开更多
It is very slow at present to reconstruct an image from its sparse decomposition results.To overcome this one of the main drawbacks in image sparse decomposition,the property of the energy distribution of atoms is stu...It is very slow at present to reconstruct an image from its sparse decomposition results.To overcome this one of the main drawbacks in image sparse decomposition,the property of the energy distribution of atoms is studied in this paper.Based on the property that energy of most atoms is highly concentrated,an algorithm is proposed to fast reconstruct an image from atoms’parameters by limiting atom reconstruction calculating within the atom energy concentrating area.Moreover,methods for fast calculating atom energy and normalization are also put forward.The fast algorithm presented in this paper improves the speed of the image reconstructing by approximately 32 times without degrading the reconstructed image quality.展开更多
Because of the broad application of multilevel converters in the high-power area,a cascaded multilevel voltage-source inverter with phase-shifted SPWM(PS-SPWM)switching scheme is proposed as a static syn-chronous comp...Because of the broad application of multilevel converters in the high-power area,a cascaded multilevel voltage-source inverter with phase-shifted SPWM(PS-SPWM)switching scheme is proposed as a static syn-chronous compensator(STATCOM).This can eliminate the bulky and weighty transformers and reduce power loss.In addition,the equivalent carrier frequency can be doubled and the output harmonics will be reduced compared with the STATCOM being put into operation.The operating principle and control methods are analyzed in detail and the feasibility is validated by simulation with MATLAB.展开更多
The chaotic motion characteristics are expounded by taking the Duffing equation system as an example.The frequency band segmentation ability and the frequency resolution of the orthogonal multiresolution analysis and ...The chaotic motion characteristics are expounded by taking the Duffing equation system as an example.The frequency band segmentation ability and the frequency resolution of the orthogonal multiresolution analysis and the orthogonal wavelet packet analysis are compared.A new orthogonal wavelet packet analysis-based chaos recognition method for chaotic motion characteristics is put forward.The chaotic,random,and periodic motions are identified effectively by use of the subfrequency band energy distribution in the signal spectrum.The characteristic frequency of chaotic motion is thus extracted.展开更多
The specificity of protein-DNA interactions is most commonly modeled using position weight matrices （PWMs）. First introduced in 1982, they have been adapted to many new types of data and many different approaches ha...The specificity of protein-DNA interactions is most commonly modeled using position weight matrices （PWMs）. First introduced in 1982, they have been adapted to many new types of data and many different approaches have been developed to determine the parameters of the PWM. New high-throughput technologies provide a large amount of data rapidly and offer an unprecedented opportunity to determine accurately the specificities of many transcription factors （TFs）. But taking full advantage of the new data requires advanced algorithms that take into account the biophysical processes involved in generating the data. The new large datasets can also aid in determining when the PWM model is inadequate and must be extended to provide accurate predictions of binding sites. This article provides a general mathematical description of a PWM and how it is used to score potential binding sites, a brief history of the approaches that have been developed and the types of data that are used with an emphasis on algorithms that we have developed for analyzing high-throughput datasets from several new technologies. It also describes extensions that can be added when the simple PWM model is inadequate and further enhancements that may be necessary, it briefly describes some applications of PWMs in the discovery and modeling of in vivo regulatory networks.展开更多
This paper introduces an idea of generating a kernel from an arbitrary function by embedding the training samples into the function.Based on this idea,we present two nonlinear feature extraction methods:generating ker...This paper introduces an idea of generating a kernel from an arbitrary function by embedding the training samples into the function.Based on this idea,we present two nonlinear feature extraction methods:generating kernel principal component analysis(GKPCA)and generating kernel Fisher discriminant(GKFD).These two methods are shown to be equivalent to the function-mapping-space PCA(FMS-PCA)and the function-mapping-space linear discriminant analysis(FMS-LDA)methods,respectively.This equivalence reveals that the generating kernel is actually determined by the corresponding function map.From the generating kernel point of view,we can classify the current kernel Fisher discriminant(KFD)algorithms into two categories:KPCA+LDA based algorithms and straightforward KFD(SKFD)algorithms.The KPCA+LDA based algorithms directly work on the given kernel and are not suitable for non-kernel functions,while the SKFD algorithms essentially work on the generating kernel from a given symmetric function and are therefore suitable for non-kernels as well as kernels.Finally,we outline the tensor-based feature extraction methods and discuss ways of extending tensor-based methods to their generating kernel versions.展开更多
With the increasing scale of information technology(IT)service system,traditional thresholdbased static service level management(SLM)solution appears to be inadequate to meet current increasingly management requiremen...With the increasing scale of information technology(IT)service system,traditional thresholdbased static service level management(SLM)solution appears to be inadequate to meet current increasingly management requirement of SLM.Due to the stochastic service request rate,the random inherent failure and load surge of IT devices during service operating stage of large scaled IT system,service level objective(SLO)maintenance issue has become a realistic and important issue in dynamic SLM.This paper proposes a closed-loop feedback control mechanism to adaptively maintain SLO that service provider(SP)guaranteed at service operation stage.The mechanism can automatically tune the capacity of IT infrastructure according to service performance dispersion and reduce SLO violations.Considering that the tuning operations also affect service performance,fuzzy control is applied to alleviate the negative effect caused by tuning operations.In the dynamic SLM system that is applied with this mechanism compared with the traditional threshold-based solution,it is proved that the amount of SLO violations obviously decreases,the reliability of the service system increases relatively,and the resource utilization of IT infrastructure is optimized.展开更多
This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters.Then,the neighborhood-roughset-based weighted feature set is proposed.The experiments o...This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters.Then,the neighborhood-roughset-based weighted feature set is proposed.The experiments of the algorithms mentioned above indicate that they have consistency,which raises a new weighted kernel.The experiment shows that better classification rate can be achieved.展开更多
The temperature distribution of typical n-type polycrystalline silicon thin film transistors under selfheating(SH)stress is studied by finite element analysis.From both steady-state and transient thermal simulation,th...The temperature distribution of typical n-type polycrystalline silicon thin film transistors under selfheating(SH)stress is studied by finite element analysis.From both steady-state and transient thermal simulation,the influence of device power density,substrate material,and channel width on device temperature distribution is analyzed.This study is helpful to understand the mechanism of SH degradation,and to effectively alleviate the SH effect in device operation.展开更多
On the basis of opto-mechanical effect and micro electromechanical system(MEMS)technology,a novel substrate-free focal plane array(FPA)with the thermal isolated structure for uncooled infrared imaging is developed,eve...On the basis of opto-mechanical effect and micro electromechanical system(MEMS)technology,a novel substrate-free focal plane array(FPA)with the thermal isolated structure for uncooled infrared imaging is developed,even as alternate evaporated Au on SiN cantilever is used for thermal isolation.A human thermal image is obtained successfully by using the infrared imaging system composed of the FPA and optical detecting system.The experiment results show that the realization of thermal isolation structure in substrate-free FPA increases the temperature rise of the deflecting leg effectively,whereas the noise equivalent temperature difference(NETD)is about 200 mK.展开更多
Emotion plays an essential role in the adaptation and social communication of organisms.Similarly,an appro-priately timed and clearly expressed emotion is a central requirement for believable interactive virtual human...Emotion plays an essential role in the adaptation and social communication of organisms.Similarly,an appro-priately timed and clearly expressed emotion is a central requirement for believable interactive virtual humans.Presently,incorporating emotion into virtual humans has gained increasing attention in the academia and industry.This strong interest is driven by a wide spectrum of promising applications in many areas such as virtual reality,e-learning,entertainment,etc.This paper introduces an emotion model of artificial psychology,in which the transition of emotion can be viewed as a Markov process and the relation of emotion,external incentive and personality can be described by a Markov decision process(MDP).In order to demonstrate the approach,this paper integrates the emotion model into a system composed of voice recognition and a realistic facial model.Thus,the model could be used for generating a variety of emotional expressions of autonomous,interactive virtual human beings.展开更多
Identification of human subjects using a geometric approach to complexity analysis of behavioural data is designed to provide a basis for a more precise diagnosis leading towards personalised medicine. Methods： The a...Identification of human subjects using a geometric approach to complexity analysis of behavioural data is designed to provide a basis for a more precise diagnosis leading towards personalised medicine. Methods： The approach is based on capturing behavioural time-series that can be characterized by a fractional dimension using non-invasive longer-time acquisitions of heart rate, perfusion, blood oxygenation, skin temperature, relative movement and steps frequency. The geometry based approach consists in the analysis of the area and centroid of convex hulls encapsulating the behavioural data represented in Euclidian index spaces based on the scaring properties of the self-similar normally distributed behavioural time-series of the above mentioned quantities. Results： An example demonstrating the presented approach of behavioural fingerprinting is provided using sensory data of eight healthy human subjects based on approximately fifteen hours of data acquisition. Our results show that healthy subjects can be factorized to different similarity groups based on a particular choice of a convex hull in the corresponding Euclidian space. One of the results indicates that healthy subjects share only a small part of the convex hull pertaining to a highly trained individual from the geometric comparison point of view. Similarly, the presented pair-wise individual geometric similarity measure indicates large differences among the subjects suggesting the possibility of neuro-fingerprinting. Conclusions： Recently introduced multi-channel body-attached sensors provide a possibility to acquire behavioural time-series that can be mathematically analysed to obtain various objective measures of behavioural patterns yielding behavioural diagnoses favouring personalised treatments of, e.g., neuropathologies or aging.展开更多
In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combinat...In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combination of tabu search （TS） algorithm and artificial neural network （ANN） in the proposed method to find out the best placement locations for IPFC in a given multi transmission line system. TS algorithm is an optimization algorithm and we use it in the proposed method to determine the optimum bus combination using line data. Then, using the optimum bus combination, the neural network is trained to find out the best placement locations for IPFC. Finally, IPFC is connected at the best locations indicated by the neural network. Furthermore, using Newton-Raphson load flow algorithm, the transmission line loss of the IPFC connected bus is analyzed. The proposed methodology is implemen- ted in MATLAB working platform and tested on the IEEE-14 bus system. The output is compared with the genetic algorithm （GA） and general load flow analysis. The results are validated with Levenberg-Marquardt back propagation and gradient descent with momentum network training algorithm.展开更多
文摘Background： Most eukaryotic protein-coding genes exhibit alternative cleavage and polyadenylation （APA）, resulting in mRNA isoforms with different 3＇ untranslated regions （3＇ UTRs）. Studies have shown that brain cells tend to express long 3＇ UTR isoforms using distal cleavage and polyadenylation sites （PASs）. Methods： Using our recently developed, comprehensive PAS database PolyA_DB, we developed an efficient method to examine APA, named Significance Analysis of Alternative Polyadenylation using RNA-seq （SAAP-RS）. We applied this method to study APA in brain cells and neurogenesis. Results： We found that neurons globally express longer 3＇ UTRs than other cell types in brain, and microglia and endothelial cells express substantially shorter 3＇ UTRs. We show that the 3＇ UTR diversity across brain cells can be corroborated with single cell sequencing data. Further analysis of APA regulation of 3＇ UTRs during differentiation of embryonic stem cells into neurons indicates that a large fraction of the APA events regulated in neurogenesis are similarly modulated in myogenesis, but to a much greater extent. Conclusion： Together, our data delineate APA profiles in different brain cells and indicate that APA regulation in neurogenesis is largely an augmented process taking place in other types of cell differentiation.
基金The research presented in this paper was supported in part by the National Natural Science Foundation of China(Grant Nos.60274011,60574087,60704008,and 90924001)the National High Technology Research and Development Program of China(Grant No.2007AA04Z154)+2 种基金the Program for New Century Excellent Talents in University(NCET-04-0094)the Specialized Research Fund for the Doctoral Program of Higher Education(20070003110)the 111 International Collaboration Project(B06002).
文摘Resource planning for a remanufacturing system is in general extremely difficult in terms of problem size,uncertainties,complicated constraints,etc.In this paper,we present a new method based on constrained ordinal optimization(COO)for remanufacturing planning.The key idea of our method is to estimate the feasibility of plans by machine learning and to select a subset with the estimated feasibility based on the procedure of horse racing with feasibility model(HRFM).Numerical testing shows that our method is efficient and effective for selecting good plans with high probability.It is thus a scalable optimization method for large scale remanufacturing planning problems with complicated stochastic constraints.
基金This work was supported by the National Natural Science Foundation of China(Grant No.60772092).
文摘This study attempted to accurately segment the mammographic masses and distinguish malignant from benign tumors.An adaptive region growing algorithm with hybrid assessment function combined with maximum likelihood analysis and maximum gradient analysis was developed in this paper.In order to accommodate different situations of masses,the likelihood and the edge gradients of segmented masses were weighted adaptively by the use of information entropy.106 benign and 110 malignant tumors were included in this study.We found that the proposed algorithm obtained segmentation contour more accurately and delineated the tumor body as well as tumor peripheral regions covering typical mass boundaries and some spiculation patterns.Then the segmented results were evaluated by the classification accuracy.42 features including age,intensity,shape and texture were extracted from each segmented mass and support vector machine(SVM)was used as a classifier.The classification accuracy was evaluated using the area(A_(z))under the receiver operating characteristic(ROC)curve.It was found that the maximum likelihood analysis achieved an A_(z)value of 0.835,the maximum gradient analysis got an A_(z)value of 0.932 and the hybrid assessment function performed the best classification result where the value of A_(z)was 0.948.In addition,compared with traditional region growing algorithm,our proposed algorithm is more adaptive and provides a better performance for future works.
文摘Ultra-shallow Si p^(+)n junctions formed by plasma doping are characterized by electrochemical capacitance-voltage(ECV).By comparing ECV results with those of secondary ion mass spectroscopy(SIMS),it is found that the dopant concentration profiles in heavily-doped p+layer as well as junction depths measured by ECV are in good agreement with those measured by SIMS.However,the ECV measurement of dopant concentration in the underlying lightly doped n-type substrate is significantly influenced by the upper heavily-doped layer.The ECV technique is also easy to control and reproduce.The ECV results of ultra-shallow junctions(USJ)formed by plasma doping followed by different annealing processes show that ECV is capable of reliably characterizing a Si USJ with junction depth as low as 10 nm,and dopant concentration up to 10^(21) cm^(-3).Also,its depth resolution can be as fine as 1 nm.Therefore,it shows great potential in application for characterizing USJ in the sub-65 nm technology node CMOS devices.
基金supported by the National Natural Science Foundation of China(Grant No.60374026)the Science and Technology Research Foundation of Heilongjiang Education Department(11523037),Automation Control Key Laboratory of Heilongjiang University.
文摘An online noise variance estimator for multi-sensor systems with unknown noise variances is proposed by using the correlation method.Based on the Riccati equa-tion and optimal fusion rule weighted by scalars for state components,a self-tuning component decoupled informa-tion fusion Kalman filter is presented.It is proved that the filter converges to the optimal fusion Kalman filter in a realization by dynamic error system analysis method,so that it has asymptotic optimality.Its effectiveness is demon-strated by simulation for a tracking system with 3 sensors.
文摘Background： Sequence-specific binding by transcription factors （TFs） plays a significant role in the selection and regulation of target genes. At the protein：DNA interface, amino acid side-chains construct a diverse physicochemical network of specific and non-specific interactions, and seemingly subtle changes in amino acid identity at certain positions may dramatically impact TF：DNA binding. Variation of these specificity-determining residues （SDRs） is a major mechanism of functional divergence between TFs with strong structural or sequence homology. Methods： In this study, we employed a combination of high-throughput specificity profiling by SELEX and Spec-seq, structural modeling, and evolutionary analysis to probe the binding preferences of winged helix-turn-helix TFs belonging to the OmpR sub-family in Escherichia coil Results： We found that E. coli OmpR paralogs recognize tandem, variably spaced repeats composed of＂GT-A＂ or ＂GCT＂-containing half-sites. Some divergent sequence preferences observed within the ＂GT-A＂ mode correlate with amino acid similarity; conversely, ＂GCT＂-based motifs were observed for a subset of paralogs with low sequence homology. Direct specificity profiling of a subset of OmpR homologues （CpxR, RstA, and OmpR） as well as predicted ＂SDR-swap＂ variants revealed that individual SDRs may impact sequence preferences locally through direct contact with DNA bases or distally via the DNA backbone. Conclusions： Overall, our work provides evidence for a common structural code for sequence-specific wHTH：DNA interactions, and demonstrates that surprisingly modest residue changes can enable recognition of highly divergent sequence motifs. Further examination of SDR predictions will likely reveal additional mechanisms controlling the evolutionary divergence of this important class of transcriptional regulators.
文摘Much of our current knowledge of biology has been constructed based on population-average measurements. However, advances in single-cell analysis have demonstrated the omnipresent nature of cell-to-cell variability in any population. On one hand, tremendous efforts have been made to examine how such variability arises, how it is regulated by cellular networks, and how it can affect cell-fate decisions by single cells. On the other hand, recent studies suggest that the variability may carry valuable information that can facilitate the elucidation of underlying regulatory networks or the classification of cell states. To this end, a major challenge is determining what aspects of variability bear significant biological meaning. Addressing this challenge requires the development of new computational tools, in conjunction with appropriately chosen experimental platforms, to more effectively describe and interpret data on cell- cell variability. Here, we discuss examples of when population heterogeneity plays critical roles in determining biologically and clinically significant phenotypes, how it serves as a rich information source of regulatory mechanisms, and how we can extract such information to gain a deeper understanding of biological systems.
基金supported by the National Hi-Tech Research and Development Program of China (Nos.2007AA01Z429,2007AA01Z405)the National Natural Science Foundation of China (Grant Nos.60633020,60573036,60702059,60503012,90204012,and 60803151)the Scientific and Technical Key Program of Tianjin (No.06YFGZGX17500).
文摘Designing reliability differentiated services for missions with different reliability requirements has become a hot topic in wireless sensor networks.Combined with a location-based routing mechanism,a quantified model without full network topology is proposed to evaluate reliability.By introducing a virtual reference point,the data transfer is limited in a specified area.The reliability function of the area is given.A detailed analysis shows that the function increases quadratically with the distance between the source node and the reference node.A reliability differentiated service mechanism is then proposed.The simulation results show the efficiency of the proposed mechanism.
基金supported by the National Natural Science Foundation of China(Grant No.60602043)China Scholarship Council Found(No.2001-3048)Applied Foundational Research of Sichuan Province(No.03JY029-048-2).
文摘It is very slow at present to reconstruct an image from its sparse decomposition results.To overcome this one of the main drawbacks in image sparse decomposition,the property of the energy distribution of atoms is studied in this paper.Based on the property that energy of most atoms is highly concentrated,an algorithm is proposed to fast reconstruct an image from atoms’parameters by limiting atom reconstruction calculating within the atom energy concentrating area.Moreover,methods for fast calculating atom energy and normalization are also put forward.The fast algorithm presented in this paper improves the speed of the image reconstructing by approximately 32 times without degrading the reconstructed image quality.
文摘Because of the broad application of multilevel converters in the high-power area,a cascaded multilevel voltage-source inverter with phase-shifted SPWM(PS-SPWM)switching scheme is proposed as a static syn-chronous compensator(STATCOM).This can eliminate the bulky and weighty transformers and reduce power loss.In addition,the equivalent carrier frequency can be doubled and the output harmonics will be reduced compared with the STATCOM being put into operation.The operating principle and control methods are analyzed in detail and the feasibility is validated by simulation with MATLAB.
基金study was supported by the 7th Younger Teacher Fund of Fok Ying Tung Education Foundation (No.71061).
文摘The chaotic motion characteristics are expounded by taking the Duffing equation system as an example.The frequency band segmentation ability and the frequency resolution of the orthogonal multiresolution analysis and the orthogonal wavelet packet analysis are compared.A new orthogonal wavelet packet analysis-based chaos recognition method for chaotic motion characteristics is put forward.The chaotic,random,and periodic motions are identified effectively by use of the subfrequency band energy distribution in the signal spectrum.The characteristic frequency of chaotic motion is thus extracted.
文摘The specificity of protein-DNA interactions is most commonly modeled using position weight matrices （PWMs）. First introduced in 1982, they have been adapted to many new types of data and many different approaches have been developed to determine the parameters of the PWM. New high-throughput technologies provide a large amount of data rapidly and offer an unprecedented opportunity to determine accurately the specificities of many transcription factors （TFs）. But taking full advantage of the new data requires advanced algorithms that take into account the biophysical processes involved in generating the data. The new large datasets can also aid in determining when the PWM model is inadequate and must be extended to provide accurate predictions of binding sites. This article provides a general mathematical description of a PWM and how it is used to score potential binding sites, a brief history of the approaches that have been developed and the types of data that are used with an emphasis on algorithms that we have developed for analyzing high-throughput datasets from several new technologies. It also describes extensions that can be added when the simple PWM model is inadequate and further enhancements that may be necessary, it briefly describes some applications of PWMs in the discovery and modeling of in vivo regulatory networks.
基金supported by the Program for New Century Excellent Talents in University of China,the NUST Outstanding Scholar Supporting Program,and the National Natural Science Foundation of China(Grant No.60973098).
文摘This paper introduces an idea of generating a kernel from an arbitrary function by embedding the training samples into the function.Based on this idea,we present two nonlinear feature extraction methods:generating kernel principal component analysis(GKPCA)and generating kernel Fisher discriminant(GKFD).These two methods are shown to be equivalent to the function-mapping-space PCA(FMS-PCA)and the function-mapping-space linear discriminant analysis(FMS-LDA)methods,respectively.This equivalence reveals that the generating kernel is actually determined by the corresponding function map.From the generating kernel point of view,we can classify the current kernel Fisher discriminant(KFD)algorithms into two categories:KPCA+LDA based algorithms and straightforward KFD(SKFD)algorithms.The KPCA+LDA based algorithms directly work on the given kernel and are not suitable for non-kernel functions,while the SKFD algorithms essentially work on the generating kernel from a given symmetric function and are therefore suitable for non-kernels as well as kernels.Finally,we outline the tensor-based feature extraction methods and discuss ways of extending tensor-based methods to their generating kernel versions.
基金Acknowledgements This work was partly supported by the State Key Development Program for Basic Research of China(No.2007CB310703)the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(Grant No.60821001)the National High Technology Research and Development Program of China(No.2008AA01Z201).
文摘With the increasing scale of information technology(IT)service system,traditional thresholdbased static service level management(SLM)solution appears to be inadequate to meet current increasingly management requirement of SLM.Due to the stochastic service request rate,the random inherent failure and load surge of IT devices during service operating stage of large scaled IT system,service level objective(SLO)maintenance issue has become a realistic and important issue in dynamic SLM.This paper proposes a closed-loop feedback control mechanism to adaptively maintain SLO that service provider(SP)guaranteed at service operation stage.The mechanism can automatically tune the capacity of IT infrastructure according to service performance dispersion and reduce SLO violations.Considering that the tuning operations also affect service performance,fuzzy control is applied to alleviate the negative effect caused by tuning operations.In the dynamic SLM system that is applied with this mechanism compared with the traditional threshold-based solution,it is proved that the amount of SLO violations obviously decreases,the reliability of the service system increases relatively,and the resource utilization of IT infrastructure is optimized.
基金This work was supported by the National High Technology Research and Development Program of China(Grant No.2009AA01Z430)the Natural Science Foundation of Beijing(No.9092009)the National Science and Technology Major Program(2009ZX03004-003-03).
文摘This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters.Then,the neighborhood-roughset-based weighted feature set is proposed.The experiments of the algorithms mentioned above indicate that they have consistency,which raises a new weighted kernel.The experiment shows that better classification rate can be achieved.
基金supported by the National Natural Science Foundation of China (Grant No.60406001).
文摘The temperature distribution of typical n-type polycrystalline silicon thin film transistors under selfheating(SH)stress is studied by finite element analysis.From both steady-state and transient thermal simulation,the influence of device power density,substrate material,and channel width on device temperature distribution is analyzed.This study is helpful to understand the mechanism of SH degradation,and to effectively alleviate the SH effect in device operation.
基金supported by the National Natural Science Foundation of China(Grant No.60236010)the National Technology Research Development Program of China(No.2005AA404210).
文摘On the basis of opto-mechanical effect and micro electromechanical system(MEMS)technology,a novel substrate-free focal plane array(FPA)with the thermal isolated structure for uncooled infrared imaging is developed,even as alternate evaporated Au on SiN cantilever is used for thermal isolation.A human thermal image is obtained successfully by using the infrared imaging system composed of the FPA and optical detecting system.The experiment results show that the realization of thermal isolation structure in substrate-free FPA increases the temperature rise of the deflecting leg effectively,whereas the noise equivalent temperature difference(NETD)is about 200 mK.
基金supported by the National Natural Science Foundation of China(Grant No.60573059)Beijing Key Laboratory of Modern Information Science and Network Technology(No.TDXX0503)and Key Foundation of USTB.
文摘Emotion plays an essential role in the adaptation and social communication of organisms.Similarly,an appro-priately timed and clearly expressed emotion is a central requirement for believable interactive virtual humans.Presently,incorporating emotion into virtual humans has gained increasing attention in the academia and industry.This strong interest is driven by a wide spectrum of promising applications in many areas such as virtual reality,e-learning,entertainment,etc.This paper introduces an emotion model of artificial psychology,in which the transition of emotion can be viewed as a Markov process and the relation of emotion,external incentive and personality can be described by a Markov decision process(MDP).In order to demonstrate the approach,this paper integrates the emotion model into a system composed of voice recognition and a realistic facial model.Thus,the model could be used for generating a variety of emotional expressions of autonomous,interactive virtual human beings.
文摘Identification of human subjects using a geometric approach to complexity analysis of behavioural data is designed to provide a basis for a more precise diagnosis leading towards personalised medicine. Methods： The approach is based on capturing behavioural time-series that can be characterized by a fractional dimension using non-invasive longer-time acquisitions of heart rate, perfusion, blood oxygenation, skin temperature, relative movement and steps frequency. The geometry based approach consists in the analysis of the area and centroid of convex hulls encapsulating the behavioural data represented in Euclidian index spaces based on the scaring properties of the self-similar normally distributed behavioural time-series of the above mentioned quantities. Results： An example demonstrating the presented approach of behavioural fingerprinting is provided using sensory data of eight healthy human subjects based on approximately fifteen hours of data acquisition. Our results show that healthy subjects can be factorized to different similarity groups based on a particular choice of a convex hull in the corresponding Euclidian space. One of the results indicates that healthy subjects share only a small part of the convex hull pertaining to a highly trained individual from the geometric comparison point of view. Similarly, the presented pair-wise individual geometric similarity measure indicates large differences among the subjects suggesting the possibility of neuro-fingerprinting. Conclusions： Recently introduced multi-channel body-attached sensors provide a possibility to acquire behavioural time-series that can be mathematically analysed to obtain various objective measures of behavioural patterns yielding behavioural diagnoses favouring personalised treatments of, e.g., neuropathologies or aging.
文摘In this paper, an interline power flow controller （IPFC） is used for controlling multi transmission lines. However, the optimal placement of IPFC in the transmis-sion line is a major problem. Thus, we use a combination of tabu search （TS） algorithm and artificial neural network （ANN） in the proposed method to find out the best placement locations for IPFC in a given multi transmission line system. TS algorithm is an optimization algorithm and we use it in the proposed method to determine the optimum bus combination using line data. Then, using the optimum bus combination, the neural network is trained to find out the best placement locations for IPFC. Finally, IPFC is connected at the best locations indicated by the neural network. Furthermore, using Newton-Raphson load flow algorithm, the transmission line loss of the IPFC connected bus is analyzed. The proposed methodology is implemen- ted in MATLAB working platform and tested on the IEEE-14 bus system. The output is compared with the genetic algorithm （GA） and general load flow analysis. The results are validated with Levenberg-Marquardt back propagation and gradient descent with momentum network training algorithm.
