The comparison of homologous sequences from different species is an essential approach to reconstruct the evolutionary history of species and of the genes they harbour in their genomes. Several complete mitochondrial and nuclear genomes are now available, increasing the importance of using multiple sequence alignment algorithms in comparative genomics. MtDNA has long been used in phylogenetic analysis and errors in the alignments can lead to errors in the interpretation of evolutionary information. Although a large number of multiple sequence alignment algorithms have been proposed to date, they all deal with linear DNA and cannot handle directly circular DNA. Researchers interested in aligning circular DNA sequences must first rotate them to the "right" place using an essentially manual process, before they can use multiple sequence alignment tools.In this paper we propose an efficient algorithm that identifies the most interesting region to cut circular genomes in order to improve phylogenetic analysis when using standard multiple sequence alignment algorithms. This algorithm identifies the largest chain of non-repeated longest subsequences common to a set of circular mitochondrial DNA sequences. All the sequences are then rotated and made linear for multiple alignment purposes.To evaluate the effectiveness of this new tool, three different sets of mitochondrial DNA sequences were considered. Other tests considering randomly rotated sequences were also performed. The software package Arlequin was used to evaluate the standard genetic measures of the alignments obtained with and without the use of the CSA algorithm with two well known multiple alignment algorithms, the CLUSTALW and the MAVID tools, and also the visualization tool SinicView.The results show that a circularization and rotation pre-processing step significantly improves the efficiency of public available multiple sequence alignment algorithms when used in the alignment of circular DNA sequences. The resulting alignments lead to more realistic phylogenetic comparisons between species. Genomic sequence alignment tools have been playing an important role in comparative genomics and phylogenetic reconstruction. However, traditional sequence alignment algorithms based on dynamic programming are very inefficient when long genome sequences needed to be aligned. To tackle this problem several heuristic based methods have been proposed. The most popular progressive multiple sequence alignment (MSA) method is ClustalW ,2, to whThis limitation is very important since circular DNA sequence alignments are central to a number of biological problems. Every cell has some kind of genome that is circular. Prokaryotic genomes are circular and many bacteria possess extra circular DNA molecules, the plasmids. Eukaryotic cells also contain organelles which possess circular DNA molecules: the mitochondrial DNA (mtDNA) inside mitochondria in all cells; and chloroplast DNA inside chloroplasts in plant cells.Mus musculus, [MtDNA has long been used for phylogenetic analyses. In fact, the absence of recombination in this genome enables an easy and direct inference of the phylogenetic evolution and its fast mutation rate leads to a high discriminative power. Until recently, phylogenetic reconstructions were based on certain regions of the mtDNA molecule, mainly the protein-coding gene cytochrome b when comparing different species  and hypeusculus, ). By theusculus,  and 1,75usculus, . The bliSequencing, the technique employed to determine bases constituting the DNA molecule is performed in fragments, generally overlapping in the ends so that an order can be inferred for constructing the map of the molecule. But the place where a circular genome begins is totally irrelevant and arbitrary. For instance, the first team sequencing the human mtDNA  decided Algorithms for the problem of cyclic sequence alignment have already been proposed in the computer science research field. However, like optimal MSA methods, most existing optimal methods that handle this kind of sequences are very time consuming and seldom used. A simple extension of a general MSA dynamic programming algorithm can be used to compute the edit distance between two cyclic sequences, but requires a quadratic time computation complexity ,17. SeveBased on algorithms closely related to the ideas described above, two software packages have been recently proposed to align circular DNA genome sequences: the Circal package  and the , a very efficient algorithm that finds the best rotation for a set of circular genome sequences that are to be aligned. Firstly, the genomic sequences are circularized. In a second stage the best rotation is calculated based on the largest chain of non-repeated blocks that belongs to all the sequences. These maximum common blocks are obtained with the help of a generalized cyclic suffix tree, which is a new concept introduced in this work. At the end of the process, the users can visualize all the identified common blocks, obtaining a precise idea on how these regions are conserved along the genomic sequences. The new rotated sequences are made available for download and can be submitted to public available MSA tools. At the developed website, several commonly used MSA and visualizations tools are proposed.In this paper, we present the CSA tool The purpose of the proposed algorithm is to find the best rotation among all the possible rotations of each circular genome sequence, in order to improve subsequent multiple sequence genome alignment. Unlike previous algorithms that pursued the same goal, the proposed algorithm is, to the best of our knowledge, the first one that is able to do this task in linear time. This was accomplished by employing the highly efficient suffix tree data structure .In general terms, a suffix tree for a given string is an advanced data structure shaped like an upside down tree that stores all the suffixes of the string and that can be used to efficiently solve many complex string problems. An in-depth explanation of this data structure is outside the scope of this article, but a detailed overview of suffix trees including construction methods and applications can be found in a number of sources (e.g. ). In thicyclic suffix tree. A cyclic suffix tree is a suffix-tree-like structure which represents all the rotations of the sequence . The construction algorithm follows Ukkonen's suffix tree construction method [suffix links and open leaves  sequence. This position-based colouring is more interesting than a length based colouring because it allows, in a much more easy way, the detection of block transpositions among sequences. Before clicking on the alignment image, the table on the right shows the blocks sorted by their length. By left-clicking over a specific section of one of the sequences in the alignment map, the positions table automatically sorts its rows to reflect the correct order of the blocks inside that sequence and it automatically scrolls itself to show the information of the blocks from the selected region/sequence. All the previous described data are available for download at the end of the page.At the CSA tool web page the user can also find a user manual, the algorithm source code and some example sequences.Drosophila melanogaster, the Gallus gallus and the Crocodylus niloticus)  were also conducted. For these sets, the alignment scores and the consensus length obtained when using the ClustalW tool with and without the CSA algorithm were compared.We also tried to compare the results obtained with the CSA tool followed by a linear DNA multiple sequence aligner, with the results obtained by the algorithms available at the Cyclope package . HoweverAfter pre-processing the set of Primate sequences with CSA, 58 homologous chains of blocks with size 8 or bigger were observed, with the biggest one consisting in a block of 16 bp followed by a gap of one base, a second block of 29 bp followed by a gap of 9 bp and a third block of 15 bp, which matches perfectly the tRNA-Met Figure . The thiNote, however, that when more distantly related sequences are considered, the common blocks correspond to single blocks of small sizes (more or less 8 bp) that are still statistical significant if mitochondrial DNA is being considered but not true for DNA sequences of bacterial genomes with million base pairs. In this way, additional care must be taken in the analysis of the sizes of the identified common blocks, when using this algorithmic approach with larger circular genomes from distantly related organisms. In these cases we are dealing with the multiple sequence alignment problem of distantly related genomes that is still an open problem.Some biological properties can help in the evaluation of the alignment results: (1) unique deletion of multiple bases instead of multiple deletions interspersing individual nucleotides; (2) higher ratio transition/transversion, as substitutions between the same type of bases are commonest than between different types; (2) the triplet-constraint in protein-coding genes making it more probable to have deletion in multiples of three than other.As can be observed in Table When comparing different alignment tools, ClustalW adds considerable lower amounts of indels than MAVID. A probable cause for this is that MAVID was especially designed for the alignment of large genomes, while ClustalW is much more conservative and takes longer to achieve results.We tried to investigate where indels were being introduced. This can be visually checked in the tool SinicView, as displayed in Figures When the third set was used so that each sequence was cut each time in different random positions, resulting in 50 test sets of 19 sequences each, the efficiency improvement of CSA was also evident. It was shown that when using the CSA tool on these sets, they all resulted in the same alignment and its score greatly outperformed the scores of each not CSA-processed test set. Figure We have demonstrated that the essential step of circularizing and rotating the mtDNA molecules prior to its alignment can significantly improve the efficiency of current multiple sequence alignment tools, developed for the alignment of linear DNA molecules. This pre-processing step leads to more accurate phylogenetic comparisons between species.To the best of our knowledge the CSA tool is the only web based tool that obtains the best rotation of a set of circular DNA sequences in a very efficient way. The new rotated sequences are made available for further processing and a picture of all conserved block for all the sequences can be found at the result page and can be viewed as a first draft of a future multiple sequence alignment.Future developments of alignment tools should include more real biological mutation constraints, enabling the use of different assumptions in the different parts of the molecules. It is clear that as sequencing strategies advance further, more information will be obtained for complete genomes, which have necessarily a diverse composition. This is clearly the case of the circular molecules of mtDNA and bacterial genomes being rapidly characterized. For instance, non-coding regions could have a less restrictive rate of gap opening; protein-coding genes should incorporate the rule of multiple of three gaps and be less restrictive for substitution at the third-codon position; third-dimension structure can give additional information for the rRNA and tRNA genes alignment.Project name: CSA: Cyclic DNA Sequence AlignerProject home page: Operating system(s): Platform independentProgramming language: COther requirements: noneLicense: NoneAny restrictions to use by non-academics: Free downloads and usage for academics onlyLP and ATF specified the problem and supervised the system implementation. FF implemented the algorithm and coded the application and the web interface. All authors contributed for the writing, read and approved the final manuscript.


Fluorescence microscopy is the standard tool for detection and analysis of cellular phenomena. This technique, however, has a number of drawbacks such as the limited number of available fluorescent channels in microscopes, overlapping excitation and emission spectra of the stains, and phototoxicity.We here present and validate a method to automatically detect cell population outlines directly from bright field images. By imaging samples with several focus levels forming a bright field http://sites.google.com/site/brightfieldorstainingThe proposed approach frees up a fluorescence channel, which can be used for subcellular studies. It also facilitates cell shape measurement in experiments where whole cell fluorescent staining is either not available, or is dependent on a particular experimental condition. We show that whole cell area detection results using our projected bright field images match closely to the standard approach where cell areas are localized using fluorescence, and conclude that the high contrast bright field projection image can directly replace one fluorescent channel in whole cell quantification. Matlab code for calculating the projections can be downloaded from the supplementary site:  The development of highly specific stains and probes, for example the green fluorescent protein and its derivatives, have made fluorescence microscopy the standard tool for visualization and analysis of cellular functions and phenomena. On the other hand, automated microscopes and advances in digital image analysis have enabled high-throughput studies automating the imaging procedure and cell based measurements. In fluorescence microscopy of eukaryotic cells, automated single-cell quantification can be achieved using multiple fluorescent probes and channels in a single experiment. The first fluorescence channel enables detection of stained nuclei, resulting in markers for cell locations. The second fluorescent channel visualizes the areas occupied by whole cells or cytoplasm, for example by a cytoskeletal actin stain Because of the limited number of fluorescent channels available, and because of partly overlapping excitation and emission spectra of the probes, studies involving subcellular colocalization are commonly carried out without nuclear or whole cell staining. As a consequence, cell-by-cell measurements are not possible. Single cell measurements are also difficult or even impossible in cells that are used for negative control, where the lack of fluorescence is used for the detection of some phenomena. Furthermore, there are other limitations in fluorescence microscopy, such as phototoxicity and imaging setup complexity. These problems have motivated the search for alternate methods to replace at least some of the fluorescence channels with standard transmitted light microscopy.The bright field channel, although readily available in all microscopes, is often neglected in cell population studies. Firstly, the cells are often nearly transparent, making the contrast very poor. Even by manual visual cell analysis it is often impossible to reliably detect the locations of cell borders, especially if the cells are clumped together. Furthermore, since no specific staining is applied, subcellular phenomena cannot be detected and nuclei are often only faintly visible. Recently, however, a number of studies have been published showing the usefulness of the bright field channel in cell detection and automated image analysis of cell populations. In Quantitative Phase Microscopy, a phase map of samples is estimated from bright field images of different focus levels We introduce and validate The resulting projections are shown to enable whole cell segmentation if only nuclear staining or other marker, such as manual cell marking for each cell is available, removing the need for an additional fluorescent channel for whole cell detection.To evaluate the performance of projection based methods, we acquired test image data by culturing and imaging bone marrow macrophages (BMM). The macrophages isolated from BL6 were cultured on glass cover slip in RPMI medium, supplemented with 10% fetal bovine serum, 100 u/ml penicillin, 100 ug/ml streptomycin, 2 mM GlutaMAX and 50 ng/ml m-CSF . The cells were stimulated with LPS 100 ng/ml for 1, 2, 4, 6, 18, and 24 hours, fixed with 3% Paraformaldehyde for 20 min and stained with BODIPY 493/503 (Invitrogen) for lipid bodies, and Sytox (Invitrogen) for nuclei. Unstimulated macrophages as well as the stimulated cells of different time points were imaged with Leica DMIRB confocal laser scanning microscope.The image stacks form eight groups with varying cell morphologies: two image sets of unstimulated macrophage cells, and a time series experiment with six groups of macrophage images from different time points during the stimulation. For each group, there are five image stacks, each consisting of three channels: 1. fluorescent nuclei 2. fluorescence subcellular stain for lipid bodies also visualizing the cytoplasm and 3. bright field channel. Each of the stacks for every channel consist of 20 individual To enable whole cell segmentation from bright field images, the contrast must be enhanced by increasing the intensity differences between cell and background areas. We achieve this by calculating different measures of variation in the The STD projection image is constructed by calculating the standard deviation of intensities in the For a more robust measure of variation we calculated IQR projection, the difference between the 75th and the 25th percentiles of the sample. That is, the lowest 25% and highest 25% of the values are first discarded, and the IQR is the range between the maximum and minimum of all the remaining intensities of In CV projection, the standard deviation of the And finally, MAD measures how much “on average” one value deviates from the median of all the values, that is, the median deviation from the median of the intensities of all the To assess the projections' sensitivity to the number of The automated image analysis and cell segmentation for the evaluation of the various projection methods was carried out by the open source CellProfiler software package For further validation, we also enumerated fluorescent spots visible in the second fluorescent channel of the stacks. The spot enumeration was done with a kernel density estimation based algorithm We did not discard cells touching image borders, although it is a procedure commonly performed to minimize bias in measurements caused by cells that are only partly visible. These cells allows us to compare segmentation accuracy also on image borders where image quality is often compromised due to nonuniform background. The computational complexity of the analysis is relatively low, taking around 4 seconds per method to calculate the projection and segment the image on a 2GHz PC with Windows Vista.http://sites.google.com/site/brightfieldorstainingAs described in the previous section, we projected stacks of bright field images into 2-D by various measures of stack For assessing the performance of the projection method, we compared automated image segmentation of whole cell areas of fluorescently stained cells to the bright field projections, and to the Annulus-method where the cytoplasm areas were estimated by annuli around the detected nuclei. We were unable to detect the cells of our whole dataset using the best previously published method in the literature for segmenting complex cell shapes in bright field images To quantify the segmentation accuracy for all the image stacks of the time series experiment, we measured the precisionFor a more compact representation of the segmentation accuracy we computed the F-score With our data set consisting of nearly 800 macrophage cells with highly complex morphologies, the overall performance of the projection methods were close to the ground truth fluorescence staining with the median F-score fluctuating around 0.8. As expected, the F-score is consistently lower for the Annulus method. More extensive plots, including F-score boxplots for each method, are given at the supplementary site. The supplementary boxplots show a number of outliers for each of the of the eight groups, for all the projection methods. In comparison to the whole dataset, the number of outliers is limited, and the effect of these outliers can be reduced, for example, by discarding the corresponding cells from further analysis, similarly as cells that are too clumped together often need to be removed from automated segmentation results. As seen from the segmentation result images (supplement) the outliers were caused by segmentation errors overestimating the whole cell areas, suggesting the area of the cell to be a suitable feature for discarding these outliers if necessary.To evaluate whether the outliers and other variations in the cell segmentation results affect the biological conclusions drawn from the data, we compared subcellular spot counts on a single cell level. By utilizing the second fluorescent channel where lipid bodies are emphasized as bright spots, we first detected the spots in the images . Then, based on the whole cell segmentation by all the projection approaches, we determined the cell to which each spot belongs. Finally, we discarded the spots outside the detected cells. This procedure enables us to estimate the effect of the different whole cell detection methods on the actual biological conclusions (spot counts per cell), since if the whole cell area detection differs dramatically from the fluorescence ground truth cell area, the numbers of spots detected in these erroneously segmented cells also change. If there is no change in spot counts, the whole cell detection is considered to have worked satisfactorily.The results for this experiment are given in Since each spot was assigned to a specific cell, we also compared the spot per cell counts for each individual cell for further validation. We have presented and evaluated different Further studies are needed for assessing generality of the projection approach. We only used images of one cell type, with low contrast all around the cells, without clearly visible cell borders. Halo effects, present in bright field images of many other cell types, for example yeast, might be emphasized erroneously in the projections. Furthermore, it would be interesting to study the segmentation performance with various cell densities and different imaging setups, and to search for optimal conditions for the imaging and subsequent analysis. Many different approaches could also be tested for preprocessing; in this work the standard Gaussian filter was found adequate, but no rigorous parameter optimization or method comparisons were performed.To fully automate the bright field cell segmentation, the markers for each cell need to be located without fluorescent nuclei, but to the best of our knowledge, there are no robust bright field based methods presented in the literature. The markers could also be set manually, but especially in high throughput studies a manual approach is not realistic. In certain studies where the cells have a very distinctive shape, such us bacteria or yeast cells, the object separation could be done based on cell shape, removing the need for a nuclear marker and thus, the need for fluorescence altogether.Bright field images are not the only stacks where the standard deviation or other projections should be studied in more detail. In fluorescence microscopy, the studied phenomenon is often visible as subcellular spots, the intensities varying according to the


The aim of this study was to investigate the effects of a massed compared to a distributed practice upon visuomotor learning as well as upon the regional oscillatory activity in the sensorimotor cortex.A continuous visuomotor tracking task was used to assess visuomotor learning; the underlying neuronal correlates were measured by means of EEG. The massed practice group completed a continuous training of 60 minutes, while the distributed practice group completed four 15 minutes practice blocks separated by rest intervals.While the massed and the distributed practice group did not differ in performance, effects of practice distribution were evident in the regional oscillatory activity. In the course of practice, the massed training group showed a higher task-related theta power and a strong task-related power decrease in the upper alpha frequency over the sensorimotor cortex compared to the distributed practice group.These differences in the regional oscillatory activity indicate a higher cognitive effort and higher attention demands in the massed practice group. The results of this study support the hypothesis, that a distributed practice is superior to a massed practice in visuomotor learning. Motor skill learning is the process by which movements or sequences of movements come to be performed with strongly reduced effort through repeated intended practice . Hence, While meanwhile it is common knowledge that motor learning induces functional and anatomical changes within neural motor circuits ,5, the iEver since the description of the alpha blockade by Hans Berger in 1924, it is known that neural activity influences the spectral composition of the EEG signal. In cortical motor areas, the power of frequency bands in the range of 10 to 20 Hz declines before and during the execution of movements as compared to a non-movement baseline condition - an effect referred to as task-related power decrease (TRPD) ,7 or eveIn the present study, participants were asked to perform a bimanual visuomotor task either following a massed or a distributed practice schedule. Based on the broad foundation provided by previous studies, we analysed task-related power changes to dissociate between the effects of the two practice schedules upon neural activity in the sensorimotor cortex. We hypothesise that over the course of practice both groups will show improvements in performance; but that the distributed practice group will perform better than the massed training group in later training stages. At the neural level, we assume that practicing the visuomotor task will lead to a diminished TRPD in the alpha and beta frequency bands, reflecting a reduction of motor-related activation due to increased task automaticity in both groups. We further hypothesise that TRPD changes in all three mentioned frequency bands observed across the practice period will differ between the two training groups, hence, reflecting the influence of practice distribution. Based on previous research, we particularly expect between-group differences in the theta frequency range. We hypothesise that the massed practice group will show a higher task-related theta power than the distributed practice group towards the end of the practice, reflecting a higher cognitive load and increased effort to maintain attention and perform accurately ,21-27.Thirty healthy right-handed female participants volunteered to participate in the present study . Handedness was assessed with the Annett-Handedness Questionnaire . A standParticipants were asked to practice a bimanual visuomotor tracking paradigm, which has been used in previous studies of our group . In ordeThe participants completed a total of 60 trials. For the statistical analysis, practice was split into groups of 15 trials corresponding to blocks 1 to 4. Each trial was initiated by the start signals "Achtung" (ready), "Fertig" (steady), "Los" (go) displayed in the middle of the screen. Subsequently the tracking commenced. Directly after each trial, participants were given feedback about their performance in form of a number displayed on the monitor indicating the mean deviation from the target track. Then a resting period of 16 seconds followed, during which a fixation cross was presented on screen. Thereafter, the next trial started automatically.Participants were randomly assigned to one of two experimental groups in counterbalanced order. One group practiced according to a massed schedule. Here, the 60 trials were conducted at one stretch without rest. In contrast, the second group practiced according to a distributed schedule that allowed three breaks of 7.5 minutes between the four practice blocks . During the resting intervals, participants of the distributed training group were presented with a commercial radio play via standard headphones (Technics Stereo Headphones RP-F550). Participants were instructed to pay attention to the radio play and press a button each time a particular character was speaking. This task was applied to prevent intentional rehearsal of the tracking movements during the rest intervals.Continuous EEG was recorded from 30 surface silver-silver chloride electrodes, positioned in accordance with the international 10-20 system and mounted with the "Easy Cap System" . The recording was referenced to FCz and impedances were kept below 5 kΩ. The BrainVision amplifier system and the BrainVision Recorder software  were used to record the data. The electrooculogram was registered by two additional electrodes located below the outer canthi of each eye. The signal was sampled at 500 Hz and bandpass-filtered from 0.5 - 70 Hz. Prior to the first and subsequent to the last practice block, five minutes of spontaneous EEG with the alternating conditions "eyes open" and "eyes closed" were recorded.The steering-wheel position at each of the 2000 data points forming the sequence was compared with the required target position. The mean absolute deviation per trial was then calculated by averaging over the registered deviation values from the 2000 data points of each trial using Matlab 6.5 . The further analysis of the behavioural data was performed using statistical analysis software SPSS . Outliers were defined as trials in which the performance differed more than two standard deviations from the mean performance of the practice block and excluded from further analysis. We then recalculated the mean performance per practice block by averaging over the remaining trials of each block. Participants that showed a significant higher performance in block 4 compared to block 1 were classified as learners (one-tailed independent samples t-test p < 0.05), while participants that did not improve significantly were classified as non-learners and excluded from further analysis .Finally, a repeated-measures ANOVA with 'block' (practice blocks 1 - 4) as within-subject factor and 'group' (massed training vs. distributed training) as between-subject factor was conducted. Greenhouse-Geisser corrections were used to prevent effects of heteroscedasticity. To further investigate the emerging main effects, subsequent t-tests were performed.P-values strongly depend on sample size we furthermore calculated effect size measures to obtain information on how strong an effect is. ETA2 (η2) is reported in multivariate ANOVA statistics and describes the variance attributed to the independent variable of interest. For the t-tests, Cohen's d , we hypothesized that participants following a distributed practice would show a stronger improvement in performance in later practice sessions as compared to the massed practice group. The behavioural data of the present study, however, do not support this hypothesis. The massed and the distributed practice group performed equally well and showed an equal amount of improvement over the course of practice. The complexity of the task used in this study may provide an explanation for this inconsistency with the findings of most previous studies. The superiority of distributed over massed practice has predominately been shown in simple motor tasks in which the temporal distribution of training sessions led to better task performance and/or longer retention -38. A meIt can also be argued that the distributed practice group did not show a superior performance compared to the massed one due to the design of the practice schedules. The length of the rest interval between practice blocks in the previous literature varies between minutes and days and an ideal rest interval has not yet been found . The metAnother possible explanation for the contrast between the finding of this study and some previous studies consists in the time point of measurement. Some of the previous studies have assessed the final skill level in a delayed retention test rather than at the end of the practice session. Dail and Christina  analysedFinally, it is conceivable that the practice of the distributed group would have to be spread over several days in order to be more effective than massed practice. Although Mackay et al.  found thIn accordance with previous ERD studies of motor behaviour ,34,40, tContrary to our expectations, a slight TRPI was found in the lower alpha band. The lower alpha band is thought to reflect general task demands and attention processes ,34. ThisIn the theta band, no systematic changes were observed over the course of practice when all learners regardless of the practice group were analyzed. Interestingly, however, we found a number of differences between the two groups with respect to practice-induced changes of the regional oscillatory theta activity. While the TRPI in theta decreased over the course of practice in the distributed practice group, the TRPI raised over the course in the massed practice group. In other words, the massed practice group showed a higher TRPI in theta than the distributed practice group in later training block, in accordance with our hypothesis. The finding of a higher task-related theta power in later training sessions in the massed practice group is in line with the previous literature linking increased theta power with increased cognition demand, increased attentional demands and increased effort ,21-24,26Furthermore, the distributed group displayed a weaker task-related power decrease in upper alpha in both clusters of electrodes in the second practice block. While lower alpha is thought to reflect general cognitive demands and attention processes, previous studies indicate that upper alpha desynchronization is related to task-specific aspects, such as for example certain aspects of motor processing . ManganoSome limitations of the present study should be noted. Firstly, all participants were female and right-handed. Future research should replicate the main findings in independent samples. Secondly, our study was focused specifically on the effects of different practice distributions upon the local activity of the sensorimotor cortex. It is conceivable that a prolonged training of a visuomotor task might additionally lead to functional changes in brain areas outside the sensorimotor cortex. This hypothesis should be tested in forthcoming studies.This study examined the effects of a massed compared to a distributed training in visuomotor learning. In the behavioural data no differences between the two groups were evident and therefore the superiority of a distributed practice could not be confirmed by the behavioural data. However, the results of this study confirm distribution of practice-effects in motor learning on the neurophysiologic level. The analysis of regional oscillatory activity indicates a higher cognitive load and increased attentional demands in the massed training group compared to the distributed training group towards the end of the practice session. It is conceivable that an elongation of the practice session would lead to exhaustion in the massed practice group resulting in a weaker learning compared to the distributed practice group. Therefore, the results of this study generally support the hypothesis, that a distributed practice is superior to a massed practice when trying to acquire a motor skill.The authors declare that they have no competing interests.BS contributed to conception and design of the study, took care of the data acquisition, performed the data analyses and interpretation and drafted the manuscript. SK contributed to the design of the study, participated in data interpretation and helped drafting the manuscript. BJ participated in the design and helped with data processing and statistical analyses. LJ contributed to the design of the study and critically revised the results. All authors read and approved the final manuscript.


The knowledge of frequency and temperature dependent dielectric properties of tissue is essential to develop ultra-wideband diagnostic technologies, such as a non-invasive temperature monitoring system during hyperthermia treatment. To this end, we characterized the dielectric properties of animal liver, muscle, fat and blood in the microwave frequency range from 0.5 GHz to 7 GHz and in the temperature range between 30 °C and 50 °C. The measured data were modeled to a two-pole Cole-Cole model and a second-order polynomial was introduced to fit the Cole-Cole parameters as a function of temperature. The parametric model provides access to the dielectric properties of tissue at any frequency and temperature in the specified range. Electromagnetic waves in the microwave frequency range offer a possibility to examine a non-transparent medium under test (MUT), because they are capable of penetrating a variety of materials, including biological tissues, without ionization. The dielectric properties determine how electromagnetic waves propagate within the MUT. The knowledge of these properties is essential for a wide variety of medical applications such as microwave breast cancer imaging ,3,4,5,6 f and temperature chnology ,13. To eA large number of studies have investigated the dielectric properties of various tissues over a wide frequency range ,16,17,18The purpose of this study is to determine the temperature dependent dielectric properties of tissue and blood. Measurements are performed by open-ended coaxial probe technique which is commonly used for dielectric spectroscopy of biological tissue . We inveThe temperature dependent dielectric properties were measured using an UWB M-sequence network analyzer (NWA) based on a one port measurement (S11) . FurtherThe temperature dependent dielectric properties are described by the complex relative permittivityIn this section we determine a temperature and frequency dependent model to reduce the size of the measured data. Furthermore, such a model enables to calculate the relative permittivity and effective conductivity at any temperature and frequency in the specified range. The frequency dependent dielectric properties of tissue are mainly characterized by the three relaxation regions, cy range . Gabrielcy range . In this overlap . For thiIn the first step we use the Levenberg-Marquart algorithm to fit the Cole-Cole parameters to the experimental data for each temperature corresponding to Equation . To limi Gabriel . First, In a second step, we use a second order polynomial to fit the temperature dependency of the Cole-Cole parameters corresponding toLazebnik . The coeFinally, the temperature dependent dielectric properties can be computed byTo quantify the quality of the fitting procedure we analyze the difference between the measured data and the results derived by the two-pole Cole-Cole model corresponding to Equation  by(6)δεThe measurements presented in this section are intended to determine the working conditions for the temperature dependent spectroscopy of tissue and blood.First, we observed the influence of the storage time between excision and measurement of porcine tissue and blood on the dielectric properties. Recent studies indicated that there is no significant difference in dielectric properties between in-vivo and ex-vivo investigations ,19,33. LIn general, we measured one and the same piece of tissue only one time in order to exclude effects due to denaturation. Therefore, we analyzed several tissue pieces from one animal spread over time from a few hours after extraction until several days after extraction. Assuming a significant influence of the storage time, a decreasing water content due to progressive dehydration would mainly influence the dielectric properties in the microwave frequency range. This effect would lead to continuously decreasing permittivity instead of the irregular behavior, as can be seen in Due to these findings, the storage time itself cannot be the origin of these differences. The intra-individual tissue differences  as well as the inter-individual differences  are much more dominant than the influence of the storage time. This knowledge and the result that all blood measurements were nearly identical g,h allowIn a first step, we investigated the dielectric properties at a constant temperature depending on the time after probe positioning. In the case of blood, the measurement procedure started directly after immersing the probe into the liquid, because the systematic error mentioned above does not occur during the measurement of blood as illustrated in In a next step, we investigate the influence of measuring the dielectric properties during the heating and the cooling cycle. The averaging of identical numbers of heating and cooling measurements ensures that the low impact of the mentioned systematic error still remaining after 30 min waiting after probe positioning will be temperature independent. This is essential to obtain reliable temperature dependencies of tissues. We use this procedure to determine the temperature dependent dielectric properties of liver, muscle and fat.In this section we present the temperature dependent properties of liver, muscle, fat and blood corresponding to the introduced temperature dependent two-pole Cole-Cole model. Due to the findings of the previous section, we applied the fitting procedure to the mean relative permittivity and mean effective conductivity over all samples for each tissue.We derived the temperature dependent Cole-Cole parameters for each temperature based on the averaged measurements see c,f, wherThe results shown in To quantify the quality of the fitting procedure, The temperature dependent Cole-Cole parameters corresponding to the measured data are shown in The temperature dependent Cole-Cole parameters based on the experimental data are depicted in The results of this section show that the dielectric properties as well as the temperature dependency are correlated to the water content of the investigated tissues. This is consistent with the fact that the dielectric properties in the microwave frequency range are dominated by the relaxation of water. The temperature dependent dielectric properties of pure water has been widely investigated by Kaatze  and Ellik et al. . The pargion see  which isgion see a. The teDue to the high water content of liver and muscle between 73% and 78%, the permittivity and the conductivity are much higher compared to fat which has a water content between 5% and 20% . FurtherIn this paper we presented a reliable measurement procedure to derive temperature dependent dielectric properties of tissue and blood. We measured the temperature dependent dielectric properties of ex-vivo porcine liver, muscle, fat and blood in the temperature range between 30 °C and 50 °C from 0.5 GHz up to 7 GHz. Furthermore, we presented a two pole Cole-Cole model combined with a second order polynomial fit to describe the frequency and temperature dependency of the dielectric properties in the specified ranges. The results of the fitting procedure agree well with the acquired data indicated by the low differences between the modeled and measured dielectric properties.Our investigations show that the dielectric properties of each type of tissue  show intra-individual as well as inter-individual differences. In comparison, porcine blood shows significant lower permittivity differences between various samples of one animal as well as between samples of different animals. Regardless of these differences, the measurements of all samples separately show a clear temperature dependence. Due to an efficient measurement procedure minimizing systematic errors, these dependencies could be reliably determined.Concerning the targeted measurement scenario of temperature monitoring during hyperthermia treatment, the intra- and inter-individual variations will not be a problem because we want to detect the changes of dielectric properties by means of UWB radar differential imaging . The knoOn the one hand, the presented results illustrate the challenge of the measurement task of non-invasive temperature monitoring inside the human body and on the other hand its feasibility with our measuring UWB technology . These f


Low-rate denial of service (LDoS) attacks reduce the quality of network service by sending periodical packet bursts to the bottleneck routers. It is difficult to detect by counter-DoS mechanisms due to its stealthy and low average attack traffic behavior. In this paper, we propose an anomaly detection method based on adaptive fusion of multiple features (MAF-ADM) for LDoS attacks. This study is based on the fact that the time-frequency joint distribution of the legitimate transmission control protocol (TCP) traffic would be changed under LDoS attacks. Several statistical metrics of the time-frequency joint distribution are chosen to generate isolation trees, which can simultaneously reflect the anomalies in time domain and frequency domain. Then we calculate anomaly score by fusing the results of all isolation trees according to their ability to isolate samples containing LDoS attacks. Finally, the anomaly score is smoothed by weighted moving average algorithm to avoid errors caused by noise in the network. Experimental results of Network Simulator 2 (NS2), testbed, and public datasets (WIDE2018 and LBNL) demonstrate that this method does detect LDoS attacks effectively with lower false negative rate. Denial of service (DoS) attacks have always been the main threats to network security . In FebrExisting researches  indicateIn response to the above limitations, we propose an anomaly detection method based on adaptive fusion of multiple features (MAF-ADM) for LDoS attacks. Time-frequency joint analysis, a powerful tool for analyzing non-stationary signals, is used to analyze the anomalies of network traffic caused by LDoS attack streams. Several statistical metrics of the time-frequency joint distribution are chosen to generate isolation trees. Then anomaly score is calculated as the basis of LDoS attack detection.The major contributions of our work are threefold. Firstly, we analyze network traffic in time-frequency domain and introduce a series of novel features for detecting LDoS attacks. These attributes can simultaneously reflect the anomalies in time domain and frequency domain. By evaluating on Network Simulator 2 (NS2) simulations, these attributes do have good sensibility to identify LDoS attacks of different parameters. Secondly, we establish isolation trees for the detection metrics and then fuse them together to describe the network state by linear weighted way. The weight of each isolation tree is dynamically adjusted according to their ability to isolate the LDoS attacks. By this way, the adaptability and accuracy of the method is further improved. Thirdly, we apply the weighted moving average algorithm to filter noise so that the method has lower false positive rate.The rest of the paper is organized as follows: P represents the attack period, R is the attack rate, and L denotes the duration of a single attack pulse.LDoS attack flow has a lower average rate than the traditional DoS attack flow, which makes it more insidious and difficult to be detected . LDoS atG is the clock granularity. RTO-based LDoS attacks: A TCP sender normally sets retransmission timeout (AIMD-based LDoS attacks: The additive increase and multiplicative decrease (AIMD) mechanism is to resend the packet immediately after the sender receives three duplicate acknowledge characters (ACKs), which reduces its congestion window (CWND) through multiplicative decrease (MD) algorithm and increases the CWND according to additive increase (AI) algorithm. The link is always in the AIMD state and does not enter the timeout retransmission and slow start under the AIMD-based LDoS attacks as It repeatedly evokes adaptive adjustment of TCP congestion control so that the network is in a fake congestion state when the attack strength Both of the above LDoS attacks exploit the TCP adaptive mechanism. The LDoS attacker usually chooses user datagram protocol (UDP) stream to launch the attack. Even if the network sends a congestion indication , UDP does not reduce the number of packets sent to the network but TCP does. Under LDoS attacks, the attack pulse stream preempts more and more network resources, and the victim believes that the network is “congested” and rapidly reduces its transmission rate. The quality of service in the network is seriously reduced as Time domain based detection algorithmMeng et al.  establisWu et al.  proposedGuo et al.  presenteTang et al.  applied Frequency domain based detection algorithmNeha et al.  proposedChen et al.  combinedWu et al.  also proWu et al.  applied There are various LDoS detection algorithms proposed in recent years. Most of them can be roughly classified into time domain and frequency domain according to detection characteristics.These existing detection methods still have some deficiencies, such as (1) high false negative rate caused by using only the characteristics of time domain or frequency domain; and (2) lack of processing of network traffic noise and adaptability. For example, the key parameters such as the detection threshold depend on experience and cannot be adjusted according to the change of network environment.To address the above limitations, a new algorithm for detecting LDoS attacks is proposed in this paper. This study is based on the fact that the time-frequency joint distribution characteristics of legitimate TCP traffic will be changed by the LDoS attacks flow. The detection features are more robust to detect different LDoS attacks since the time-frequency joint distribution can simultaneously reflect the anomalies in time domain and frequency domain. Then the anomaly score is calculated by MAF-ADM to metric that change, which is the basis of detecting LDoS attacks.In this section, we firstly describe that how to obtain time-frequency joint distribution by performing short-time Fourier transform on network traffic in the bottleneck link. The reason for that is the network will be in a state of fake congestion and network traffic in the bottleneck link will be the first to bear the brunt when an LDoS attack occurs. Some statistical features of the time-frequency joint distribution are extracted as detection features, which accurately represent the anomalies caused by LDoS attacks both in frequency domain and in time domain .In this paper, detection window is used as the basic unit for detecting LDoS attacks. Detection window is defined as a sample sequence consisting of network traffic samples Given window function of fixed time width  Formula  33]. Am,nThe matrix T, refers to the sum of the amplitude frequency of all elements in the time-frequency joint distribution matrix as Formula , named  Formula . In Figu Formula  and 5)..T, referThe segmentation frequency ratio (SFR), expressed as  Formula .(6)SLowThe normalized variance of segmentation frequency (NVSF), denoted by  Formula . (7)NLowNormalized variance comparison of each frequency part between detection window in normal state and LDoS attack state as shown in In this section, we present MAF-ADM for detecting LDoS attacks as shown in As analyzed above, we can utilize the features of time-frequency joint distribution to describe the possibility of the network suffering from LDoS attacks. It is costly that simply combined these features to construct a multi-dimension description model. Therefore, we build isolation trees for these features, which have a low linear time complexity and a small memory requirement.d characteristic dimension, the binary tree structure named isolation tree is used to separate samples containing LDoS attacks from normal samples.Since samples that containing LDoS attacks usually have the characteristics of being sparsely distributed and distant from dense normal samples, they are closer to the root node in the isolation tree structure and therefore more easily isolated.Supposing q and its value p to recursively split the training data Y until one of the following three conditions is met:The isolation tree reaches a defined height;There is only one sample on the node;Features of all the nodes are the same.The construction steps  of isolaIn , path leFor the purpose of analyzing the ability of isolation trees to isolate samples containing LDoS attacks, we also used two kinds of samples  to calculate the path length in each isolation tree. S is proposed to fuse the normalized results of all isolation trees. It ignores the difference between isolation ability of isolation trees that using mean value of the path length to calculate anomaly score. In order to more rationally synthesize the result of each isolation tree, we apply the weighted path length to instead of the mean value. Then the weight of the t isolation trees.Path length in different tree structures is not comparable, so anomaly score  Formula .(8)wjcu Formula . There aThen the anomaly score can be calculated by Formula . (10)Syi Formula  35] is  is (10)S Formula . (12)Hi=Network traffic has randomness, which means that many accidental factors, such as data stream bursts, data stream silence and occasional noise, may easily cause false positives. To solve this problem, we adopt weighted moving average algorithm to smooth anomaly score as Formula . Anomalyk as Formula  and LDoS attacks with , as shown in For verifying the detection performance of this method for LDoS attacks in the real network environment, we established a network platform as In this topology, six computers (PC1–PC6) used socket program to establish connections with the server. PC1–PC5 applied TCP protocol and PC6 adopted UDP protocol. All six computers sent packets to the server continuously. LDoS attacker reduced the quality of network service by sending high speed pulse stream periodically. We set the attack period to 1 s, and adjusted the attack intensity by changing the attack duration and rate. The attack rate was controlled by changing the number of threads. The larger the number of threads, the stronger the attack rate.We also conducted multiple sets of experiments on the testbed to evaluate the performance of our algorithm. The specific experimental parameters were set as shown in Among the four groups of test data, the method proposed in this paper could identify most of the attack data as presented in We performed experiments on the Measurement and Analysis on the WIDE Internet (WIDE2018) dataset and the Lawrence Berkeley National Laboratory (LBNL) dataset in this subsection. These datasets consisted of various speed of links from 2 Mbps to 10 Gbps. Neither of the above two datasets contained LDoS attacks, so we used only the false positive rate to evaluate the detection performance.From WIDE2018, we selected 16 days of data (from 20180101 to 20180216) and used 35 days of data (from 20180217 to 20180528) for training. In LBNL, 21 days of data were selected and the first 600 s of each day was used for training. We applied methods to classify the network traffic, and the classification results are shown in The detection method in this paper is compared with the existing algorithms for detecting LDoS attacks in recent years in terms of experimental platform, detection accuracy, false negative rate and false positive rate as shown in In this paper, we analyzed that the statistic attributes of TCP traffic in the time-frequency joint domain would be changed under LDoS attacks. Based on that, we developed MAF-ADM for LDoS attacks. On the one hand, the weighted fusion algorithm was applied to build the isolation forest according to the ability of the isolation trees to isolate samples containing LDoS attacks. On the other hand, we adopted the weighted moving average algorithm and the dynamic threshold algorithm to calculate anomaly score and threshold according to different network environments.The method we proposed could detect 100% of LDoS attacks successfully on simulation platforms NS2, which does have good sensibility to identify LDoS attacks of different parameters. Results of experiments on testbed and the public datasets also demonstrate that this method does have better adaptability in the complex real network environment and immune to normal fluctuations of the network traffic.In conclusion, the proposed method can distinguish LDoS attacks and legitimate traffic effectively. It has better adaptability, higher accuracy and lower false positive rate.In the future work, we will continue our research in two directions. First, we will put effort to study variations of LDoS attacks and how they work, such as the aggregated or synchronous low-rate distributed DoS attacks. Another promising direction we hope to achieve is the development of MAF-ADM to defend against variants of LDoS attacks and the deep integration of MAF-ADM with other network security appliances against LDoS attacks, such as intrusion detection in wireless sensor network, prevention appliance in cloud computing, and so forth.


In the aerospace field, compact optoelectronic platforms (COPs) are being increasingly equipped on unmanned aircraft systems (UAS). They assist UAS in a range of mission-specific tasks such as disaster relief, crop testing, and firefighting. However, the strict constraint of structure space makes COPs subject to multi-source disturbances. The application of a low-cost and low-precision sensor also affects the system control performance. A composite hierarchical anti-disturbance control (CHADC) scheme with multisensor fusion is explored herein to improve the motion performance of COPs in the presence of internal and external disturbances. Composite disturbance modelling combining the characteristic of wire-wound moment is presented in the inner layer. The adaptive mutation differential evolution algorithm is implemented to identify and optimise the model parameters of the system internal disturbance. Inverse model compensation and finite-time nonlinear disturbance observer are then constructed to compensate for multiple disturbances. A non-singular terminal sliding mode controller is constructed to attenuate disturbance in the outer layer. A stability analysis for both the composite disturbance compensator and the closed-loop system is provided using Lyapunov stability arguments. The phase lag-free low-pass filter is implemented to interfuse multiple sensors with different order information and achieve satisfactory noise suppression without phase lag. Experimental results demonstrate that the proposed CHADC strategy with a higher-quality signal has an improved performance for multi-source disturbance compensation. The continuing rapid development of unmanned aircraft systems (UAS) in the aerospace field has led its essential component, namely optoelectronic platforms, to evolve to a more compact and flexible type. In this way, they can be applied to a growing number of aerospace applications at a more compact size and a lower cost, including aviation planning, forest fire prevention, precision agriculture, disaster relief and public safety, among others ,2,3,4. CA wide variety of studies on anti-disturbance have been developed by researchers and practitioners in different industrial sectors to achieve a better disturbance rejection performance . The antThe disturbance suppression method aims to design a robust controller such that the system can maintain stability and good performance in the presence of disturbance and model uncertainty. The sliding mode control (SMC) is a robust method of controlling nonlinear and uncertain systems that keeps the systems insensitive and robust to uncertainties and disturbance on the sliding surface . KinematTo achieve complete control of disturbance, the disturbance observer-based control (DOBC) is designed to estimate and compensate for disturbance by filtering the differences between the control input and the ideal input using the inverse model of nominal plant . The robDisturbance model-based compensation methods establish the disturbance model according to their characteristics and the mechanism influence on the system performance and compensate for them in the feedforward loop of the controller. Maxwell-slip (GMS) friction-model-based feedforward is applied to acquire sufficiently high path and tracking accuracy . The StrThe composite hierarchical anti-disturbance control (CHADC) for complex systems with multiple disturbances has been proposed by Prof. Guo. It combines the respective advantages of disturbance compensation and disturbance suppression. The CHADC approach generally employs two layers: the inner layer, which includes the disturbance observer and the other compensator in the feedforward path, and the outer layer, which includes the disturbance attenuation controller. In the inner layer, multiple disturbances are classified and modelled according to their characteristics and the mechanism influence on the system performance. The disturbances are then targeted, evaluated and compositely compensated for. Meanwhile, the disturbance attenuation method is applied in the outer layer to suppress system equivalent disturbances, such as unmodeled dynamics, parameters and structural uncertainties . The CHACOPs are widely installed in UAS. To achieve a better imaging effect, COPs have high requirements on both system control accuracy and anti-disturbance performance. For COPs, completing all signal transmissions with conducting rings only is not possible because of the strict constraints of structure space and cost. The signal transmission between shafts is unavoidable through wires. For a more functional platform, more signal must be transmitted through wires; thus, wire-wound moment and other related disturbances are magnified on such kind of platforms. Consequently, for COPs, the identification and modelling of internal disturbance, including wire-wound moment, are urgent and necessary. The strand overall mechanical behaviour is modelled according to the Euler–Bernoulli beam theory to build a link between the structural theories for large-scale analyses of cable structures . Multi-sCOPs are subject to multiple external and internal disturbances, model and parameter uncertainties in the aerospace environment. Motivated by the idea of the CHADC scheme, this study proposes a composite hierarchical anti-disturbance control strategy for COPs. In the inner layer, it combines a feed-forward inverse model compensation based on parameter identification with the adaptive mutation differential evolution (MDE) algorithm and a finite-time nonlinear disturbance observer to compensate for multiple disturbances. The role of the feed-forward inverse model compensation is to estimate and compensate for the modellable internal disturbance. The finite-time disturbance observer aims to compensate for the effect of the external disturbance in finite time. In the outer layer, a non-singular terminal sliding mode (NTSM) is applied to attenuate disturbance and realise a high dynamic performance. Through composite disturbance estimation and compensation, the NTSM controller may take a smaller value for switching gain without sacrificing the disturbance suppression effect and chattering reduction. This hierarchical structure not only simplifies the design method, but also improves the control performance of the system. In particular, a phase lag-free low-pass filter (phase lag-free LPF) is practically applied to obtain a high-quality signal without phase lag instead of LPF. To interfuse multisensor information, the phase-lead information in the measured signal of a higher-order sensor is used to revise the phase lag in an LPF. Combined with this signal fusion method, the proposed CHADC can more effectively improve the control performance of the system. In addition, the stability of the disturbance compensator and the feedback controller is demonstrated.This paper is organised as follows: we shall first briefly discuss the motion model of COPs in The axes of the COP frame are decoupled, with each degree of freedom being a typical motion control servo system. The outer frame of the compact platform driven by a DC motor was investigated herein. The motor stator of COPs is embedded in the carrier, indicating that the stator and the carrier are fixed as a rigid body. Meanwhile, the motor rotor is connected with the outer frame through the structure part. The rotor and the frame can be considered as completely rigid when the stiffness of the structural parts is large enough. Carrier shaking disturbance is coupled with the control plant through the motion between the motor stator and the rotor.The system dynamic equations can be expressed as follows:The following equation for quations  and 2)::Mout canTherefore, according to Equations  and 4),,4), the Armature inductance is generally relatively small in COPs. Consider the dynamics induced by armature inductance as part of the internal disturbance, the order of control plant as Equation  could beModel and parameter uncertainties shown in .(7)Jp= Internal Disturbance ModellingA traditional disturbance observer was applied on a COP under a static and relatively stable environment to characterise and evaluate the internal disturbance behaviour. The DOBC, which was proposed by Prof. Ohinishi, estimates the equivalent disturbance and uses it as an offset input signal to compensate for the disturbance.The estimation capability of DOBC is related to the bandwidth of its low-pass filter according to the design principle of the disturbance observer. The disturbance observation result is more accurate when the motion frequency of the system is lower. The COP reciprocates under a 2The impact of wire-wound friction on the motion control precision for the COP will be exaggerated because a large number of wires must be placed in a restricted space for signal transmission. The motion of wire rope strands can be simplified as the torsion problem of wire ropes around the equilibrium point. Wire-wound force is generated under the influence of shock excitation when the shaft begins to move with the wire rope strands. The differential equation of the motion can be expressed as follows:Setting Equation  can be cThe general solution of the differential equation in Equation  is(12)αAccording to Euler’s formula,A when Equation  can be tEquation  and the The wire-wound moment t when the system is moving at a constant speed The position angle Equation  into (14Setting Equation  can be r(b) Disturbance Identification based on Adaptive Mutation Differential Evolution Algorithm (MDE)According to Equation , a1,a2,alligence . The proThe basic steps of this algorithm to identify and optimise the parameters in Equation  are as fGroup Initialization.i-th individual jth parameter range, respectively. If Equation . In thisDifferential Mutation.F is the mutation factor. An adaptive scaling factor is adopted as follows to avoid a premature algorithm:G is the current number of iterations; and F decreases as the number of iteration G increases to maintain the optimal solution from destruction. In the iteration process, the violated individual will be randomly regenerated within the boundary range to ensure that the generated mutation vector satisfies the boundary constraint The vector difference of two random individuals is scaled and combined with the individual vector to be mutated, as in Equation .(22)Vi Inverse Model CompensationAccording to the abovementioned analysis, the internal disturbance is associated with frame motion states For a COP, the ideal motion equation of the controlled frame without disturbance can be expressed as:The error between the expected position response g is the equivalent filter bandwidth of the disturbance observer.According to the design principle of disturbance observer(DOB) in the RIC structure ,(31)uRIHowever, a linear filter cannot effectively compensate for the nonlinearity, and the finite-time convergence of error cannot be guaranteed. A nonlinear element is introduced into Equation  herein:39), the e refers to the error between the expected output angular e based equivalent equation could then be written as follows:Based on Equations , e=xn1−xquations  and 40)e=xn1−x1.e will converge to be zero, and then the practical output will track expected output. It means that the estimated and compensated disturbance by the proposed finite-time disturbance observer will approach practical disturbance. Therefore, the finite-time convergence of the proposed disturbance observer can be proved by the error convergence of the equivalent closed-loop system.The error between the expected output and the practical output is caused by multiple disturbances including external disturbances, internal disturbances, model and structure uncertainties. When the multiple disturbances are evaluated and compensated, the error The definitions and the theorems are presented as follows to prove the finite-time stability of the system :Definition 1.(Finite-time stability) Considering the systemwhere Equation  satisfieThe finite-time stability requires not only the stability of the system, but also the finite-time convergence. The Lyapunov stability criterion for finite-time control systems is:Theorem 1.Considering the system in Definition 1, suppose that a continuous differentiable function (1) V is a positive definite function;(2) the arithmetic number c and a satisfy then, the system shown in Equation  is finitThe Lyapunov function is defined as follows:Substituting Equation  into EquLet Therefore, if According to Theorem 1, as long as the conditions in Equations  and 49)49) are gThe proposed method also has the following characteristics in the problem of anti-disturbance ability:Theorem 2.Let Equation  will be Proof. Select a continuous differentiable Lyapunov function as in Equation . The folThe final convergence domain of the proposed controller is defined as:For arbitrary Equation , for arbQ in finite time. The practical control output will track the expected output and then the estimated disturbance by the proposed finite-time disturbance observer will approach practical disturbance. The finite-time convergence of the proposed disturbance observer is proved.The analysis above proved that the error between the expected output and practical output of the equivalent closed-loop structure will converge to the stabilised region The position or velocity signal is employed as a feedback signal to realise the closed-loop control. The performance of the closed-loop control system depends on the sensor signal-to-noise ratio (SNR). The COP is restricted by the installation space and cost, and the sensor measurement accuracy is limited. For the low SNR sensor, LPFs are commonly used to improve its SNR. However, the associated phase lag will degrade the performance of the whole system.A traditional LPF is widely used as:However, its phase response in Equation  shows thThe phase lag of the filtered signal is unavoidable compared to the original signal because of the existence of a first-order inertial element in the LPF. A higher-order sensor could be used to obtain “phase lead” information.The phase lag-free LPF  with a hAfter the disturbance compensation in the inner layer, the equivalent control plant of the outer controller is presented as follows:The new state variables of the position error and its derivative are defined as follows: The state space of the outer layer can be expressed as:p and q are the positive odd integers and A non-singular terminal sliding mode method(NTSM) is designed to achieve good performances, such as fast convergence, better tracking precision and robustness to disturbance. The sliding surface  is desigThe terminal sliding mode controller can be designed as:Assumption 1.The disturbance We can then reach the following theorem:Theorem 3.If Assumption 1 holds, under the control law , the conProof. Choosing Lyapunov function Equation  yield:tfis in finite time Therefore, the position error will converge to zero along the sliding surface Practical experiments were implemented to verify the performance of the proposed system. The position signal was noisy because of cost constraints and signal interference. Two sets of experiments were performed to verify the effectiveness of the phase lag-free LPF.First, shake the COP and make it do sinusoidal motions with different frequencies and amplitude values. Acquire and compare the original position signal, LFP filtering signals and phase lag-free filtering signal . CompareIn the second experiment, the PID feedback control was applied to the COP. The experiment consisted of three cases. In case 1, the position signal was the initial signal from the position sensor. In case 2, the position signal was filtered by the LPF. In case 3, the position signal was filtered by the phase lag-free LPF with high-order sensor information. According to the test data shown in Furthermore, when working in a practical environment, the COP also suffers from external disturbance, including wind disturbance and carrier shaking. An additional simulated wind disturbance was imposed on the system to investigate the comparative performance of different compensators with multiple disturbances. The abovementioned experimental results indicated that the proposed composite disturbance compensator evidently had obvious advantages. The proposed method can effectively evaluate and compensate for the influence of the internal and external disturbances on COPs in a finite time.A set of contrast experiments between the traditional PID feedback controller with the composite disturbance compensation method and the proposed CHADC algorithm was implemented to validate the proposed composite hierarchical anti-disturbance control method on COPs.In the aerospace field, more and more compact optoelectronic platforms are being applied to unmanned aircraft systems to complete various tasks, such as automatic guidance and search. Aimed at solving the multi-source anti-disturbance problem, a composite hierarchical anti-disturbance controller with phase lag-free multisensor fusion was developed herein. The composite disturbance compensator in the inner layer was combined with a finite-time disturbance observer and internal disturbance modelling, identification and compensation with the MDE algorithm. The pre-identifiable internal disturbance was compensated for by the MDE-based internal disturbance compensator. The external disturbance was evaluated and compensated for by the finite-time disturbance observer. In the meantime, a non-singular terminal sliding mode control was introduced in the outer layer of the proposed CHADC strategy to improve the dynamic response and disturbance attenuation performances. By multisensor fusion, the phase-lead information of a higher-order sensor was adopted, and the filtered information without phase lag was achieved. Stability and performance analyses were conducted. The experiments on a COP were implemented to verify the validity of the proposal. The results highly agreed with the theoretical work and demonstrated that the proposed method achieves a satisfactory multiple disturbance rejection and a robust performance.


Background: Kinematic and muscle patterns underlying hand grasps have been widely investigated in the literature. However, the identification of a reduced set of motor modules, generalizing across subjects and grasps, may be valuable for increasing the knowledge of hand motor control, and provide methods to be exploited in prosthesis control and hand rehabilitation.Methods: Motor muscle synergies were extracted from a publicly available database including 28 subjects, executing 20 hand grasps selected for daily-life activities. The spatial synergies and temporal components were analyzed with a clustering algorithm to characterize the patterns underlying hand-grasps.Results: Motor synergies were successfully extracted on all 28 subjects. Clustering orders ranging from 2 to 50 were tested. A subset of ten clusters, each one represented by a spatial motor module, approximates the original dataset with a mean maximum error of 5% on reconstructed modules; however, each spatial synergy might be employed with different timing and recruited at different grasp stages. Two temporal activation patterns are often recognized, corresponding to the grasp/hold phase, and to the pre-shaping and release phase.Conclusions: This paper presents one of the biggest analysis of muscle synergies of hand grasps currently available. The results of 28 subjects performing 20 different grasps suggest that a limited number of time dependent motor modules (shared among subjects), correctly elicited by a control activation signal, may underlie the execution of a large variety of hand grasps. However, spatial synergies are not strongly related to specific motor functions but may be recruited at different stages, depending on subject and grasp. This result can lead to applications in rehabilitation and assistive robotics. The use of the hands is one of the most crucial capabilities for daily activities. The loss of a hand can substantially reduce the quality of life of a person, since it strongly affects physical capabilities in performing activities of daily living (ADL) and it represents a relevant social problem considering that people with a major upper limb loss were ~41,000 in USA in 2005. The number of amputees is expected to double by 2050 .The fact that a limited number of modules may account for a large variety of grasps is thus commonly deduced from the literature. A recent study by Prevete et al.  investigDespite the kinematic patterns being exploited more often for hand analysis, some studies have investigated the dimensionality reduction problem from the point of view of muscle synergies. The muscle synergy approach is based on decomposition algorithms that identify groups of co-activating muscles (synergies) that are coordinated by time-varying activation commands. The extracted patterns may be influenced by several factors regarding sEMG, including fatigue, sweating, changes in electrode or arm positioning , performing (or imagining to perform) up to 53 different hand movement , and the second one representing time-variant activation commands for each synergy (ci), as in Equation (1):The Data Analysis was fully performed with Matlab 2014a with custom-developed software. First, kinematic recordings  were used to separate movement phases. Data from 12 sEMG channels were bidirectionally high-pass filtered at 50 Hz  to remove motion artifacts, rectified, Hilbert-transformed (Matlab hilbert), low-pass filtered with a cut-off frequency of 10 Hz  to remove noise with mono-directional filtering. sEMG data from each subject and each trial were pooled in single aggregated matrices and synergies were extracted using the non-negative matrix factorization (NMF) algorithm  represents the sEMG data at time r was chosen, increasing from 1 to 50 . For each r, the NMF algorithm was applied 1,000 times in order to avoid local minima. The repetition accounting for the highest variance of the signal was chosen as the representative of order r. The number of synergies was chosen as the minimum r explaining at least 90% of the variance of the signal .In this work, the extracted synergies were included into a single cluster analysis. Grouping all the modules could lead to complex matching between each spatial component and the corresponding motor function  to 50 (maximum), was tested by repeating the algorithm 200 times and selecting the best solution for each order according to the metrics described in the following section.The Mean Euclidean Distance (MED) of the population from the reference centroids, indicating the quality of the clustering, as a synthetic index for each clustering order. The lower the Mean Euclidean Distance, the better elements fit into their cluster.When the k-means clustering procedure is applied, the number of desired clusters N must be specified. Defining as M the number of elements to be clustered , N can range between 1 and the total number of the clustered elements (1<=N<=M).N = 1, the clustering procedure classifies a population within a single group: thus, the cluster solution 1 is (implicitly) the mean of a population, and corresponds to the lowest level of precision in approximating a population with a clustering procedure. Following the previous considerations, the Normalized Euclidean Distance (NED) was computed by considering the cluster solution 1 as the source of maximum clustering error, which was set to 1. Thus, the NED for each clustering order i was computed as:When The slope of the Normalized Euclidean Distance (NED') is NED derivative. NED indicates how the precision of the cluster analysis increases when increasing the order of the clustering.The selection of the appropriate number of clusters  was made by pondering the following metrics . The threshold selected by the experimenters in this work was 5%. Consequently, the number of clusters was selected as the minimum number needed to have the NED < 0.05.The hypothesis that justifies the use of cluster analysis is that the dataset can be represented with a chosen number of cluster centroids depending on the maximum error that the experimenter is willing to accept. Depending on the application, the tolerance can be increased or reduced, describing the original dataset of motor modules with a specific level of precision .The characterization of the obtained mean spatial synergies was furtherly specified by considering all the pairwise dot products between their compositions. Each temporal component, initially associated with its respective spatial synergy, was matched to its relative centroid after cluster identification. Then, all the temporal components were averaged to extract a mean temporal component for each cluster, representing a mean activation of the spatial synergy in time. Finally, the characterization of temporal components was concluded by considering the correlations between the mean temporal components.Outcome 1: Definition of the complete dataset of extracted muscle synergies of healthy subjects in freely executed grasps; methods and statistics: NMF algorithm for factorization; 90% of the VAF + minimum slope 0.05 for each further extracted synergy.Outcome 2: Definition of cluster centroids for muscle synergies in freely executed grasps; methods and statistics: k-means clustering; lowest normalized Euclidean distance to define the number of centroids.Outcome 3a: Characterization of the spatial composition of the centroids; methods and statistics: dot products between pairwise centroids to assess their difference in composition.Outcome 3b: Characterization of the temporal features of the centroids; methods and statistics: Pearson correlations between temporal components.Given the aims of the study (see Introduction): “First, to provide a set of benchmark muscle hand synergies extracted from publicly available dataThe extracted synergy dataset is summarized in Figure The whole dataset of spatial synergies, which is composed of 966 extracted modules, was clustered according to the k-means algorithm, with a clustering order ranging from 1 to 50. Figure The results of the clustering procedure are shown in Figure An interesting result of this study is that, with the used method for synergy extraction, a number of modules ranging from 1 to 3 is sufficient for reconstructing the majority of the original sEMG in each grasp. As a consequence, a limited number of patterns is needed to achieve a grasp, which is a relevant result considering the availability of high redundancy at the muscle and kinematic level. This is seen in some patterns that are often repeated and especially in the co-activating group composed of f1-f8-finger flexors that are very often grouped together, especially in the hold phase. In most of the cases, two activation patterns are recognizable: a strong co-activation, often  corresponding to the grasp/hold phase, and two minor co-activating patterns in the pre-shaping and release phases that are often grouped in a single synergy. This result is particularly interesting considering that only two electrodes were not positioned on the forearm  and comparing the results with the results obtained by d'Avella et al.  and LiarWhile not extensively discussed in this paper, the remarkable repeatability of the temporal components might be a further motor-control feature aimed at simplifying muscle coordination, as a strategy exploited by the CNS to perform hand grasps. These results are in accordance with the previous findings in the literature, that showed that, in respect to the original dimensionality of the control, the number of modules underlying grasps is probably strongly reduced , properly elicited in time can approximate the entire dataset for all subjects with high accuracy . Ideally, each movement considered in the experiment can potentially be reproduced as a combination of spatial synergies, thus providing prostheses with higher dexterity (a higher number of movements that can be controlled) starting from a set of a few robustly controlled modules. Hand muscle synergies may be applied to high level control approaches, consisting of training subjects to reproduce and modulate the sEMG patterns that correspond to the muscular hand synergies (or combinations of them) and apply pattern recognition algorithms to recognize the results. This strategy may be an alternative to the control systems currently described in literature. As said in the introduction, robotic hands that reproduce hand movements by modulating the main postural hand synergies have already been presented in literature  and the test data (used to test it) are taken from the same distribution. However, this is not always easy, in particular when using deep learning approaches that require large amounts of data for training. To overcome distribution mismatches, transfer learning and domain adaptation approaches have been used in several domains, including computer vision . The conclusions of this article suggest that a limited number of time-dependent motor modules, correctly elicited by a control activation signal, may underlie the execution of a large variety of hand grasps. However, spatial synergies are not strongly related to a specific motor functions but have a sparse recruiting timing.AS designed the experiment, wrote the software for synergy extraction and clustering, elaborated the data, and wrote the paper. AC participated to data analysis and interpretation, and wrote the paper. LM participated to data analysis and wrote the paper. HM acquired the NinaPro database and wrote the paper. MA acquired the NinaPro database, participated in the design of the study and to data interpretation, and wrote the paper.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.