New data association technique based on ACO with directional information considered

Due to the advantages of ant colony optimization （ACO） in solving complex problems, a new data association algorithm based on ACO in a cluttered environment called DACDA is proposed. In the proposed method, the concept for tour and the length of tour are redefined. Additionally, the directional information is incorporated into the proposed method because it is one of the most important factors that affects the performance of data association. Kalman filter is employed to estimate target states. Computer simulation results show that the proposed method could carry out data association in an acceptable CPU time, and the correct data association rate is higher than that obtained by the data association （DA） algorithm not combined with directional information.

Functional connectivity and information flow in cerebral motor regions of healthy people following finger movement training

BACKGROUND：Neuro-rehabilitative training has been shown to promote motor function recovery in stroke patients,although the underlying mechanisms have not been fully clarified.OBJECTIVE：To investigate the effects of finger movement training on functional connectivity and information flow direction in cerebral motor areas of healthy people using electroencephalogram （EEG）.DESIGN,TIME AND SETTING：A self-controlled,observational study was performed at the College of Life Science and Bioengineering,Beijing University of Technology between December 2008 and April 2009.PARTICIPANTS：Nineteen healthy adults,who seldom played musical instruments or keyboards,were included in the present study.METHODS：Specific finger movement training was performed,and all subjects were asked to separately press keys with their left or right hand fingers,according to instructions.The task comprised five sessions of test train test train-test.Thirty-six channel EEG signals were recorded in different test sessions prior to and after training.Data were statistically analyzed using one-way analysis of variance.MAIN OUTCOME MEASURES：The number of effective performances,correct ratio,average response time,average movement time,correlation coefficient between pairs of EEG channels,and information flow direction in motor regions were analyzed and compared between different training sessions.RESULTS：Motor function of all subjects was significantly improved in the third test comparedwith the first test （P〈 0.01）.More than 80% of connections were strengthened in the motor-related areas following two training sessions,in particular the primary motor regions under the C4 electrode.Compared to the first test,a greater amount of information flowed from the Cz and Fcz electrodes （corresponding to supplementary motor area） to the C4 electrode in the third test.CONCLUSION：Finger task training increased motor ability in subjects by strengthening connections and changing information flow in the motor areas.These results provided a greater understanding of the mechanisms involved in motor rehabilitation.

An Improved Direction Relation Detection Model for Spatial Objects

Direction is a common spatial concept that is used in our daily life. It is frequently used as a selection condition in spatial queries. As a result, it is important for spatial databases to provide a mechanism for modeling and processing direction queries and reasoning. Depending on the direction relation matrix, an inverted direction relation matrix and the concept of direction pre- dominance are proposed to improve the detection of direction relation between objects. Direction predicates of spatial systems are also extended. These techniques can improve the veracity of direction queries and reasoning. Experiments show excellent efficiency and performance in view of direction queries.

Determination of specificity influencing residues for key transcription factor families

Transcription factors （TFs） are major modulators of transcription and subsequent cellular processes. The binding of TFs to specific regulatory elements is governed by their specificity. Considering the gap between known TFs sequence and specificity, specificity prediction frameworks are highly desired. Key inputs to such frameworks are protein residues that modulate the specificity of TF under consideration. Simple measures like mutual information （MI） to delineate specificity influencing residues （SIRs） from alignment fail due to structural constraints imposed by the three-dimensional structure of protein. Structural restraints on the evolution of the amino-acid sequence lead to identification of false SIRs. In this manuscript we extended three methods （direct information, PSICOV and adjusted mutual information） that have been used to disentangle spurious indirect protein residue-residue contacts from direct contacts, to identify SIRs from joint alignments of amino-acids and specificity. We predicted SIRs for homeodomain （HI））, helix-loop-helix, LacI and GntR families of TFs using these methods and compared to MI. Using various measures, we show that the performance of these three methods is comparable but better than MI. Implication of these methods in specificity prediction framework is discussed. The methods are implemented as an R package and available along with the alignments at http：//stormo.wustl.edu/SpecPred.