Time series classification with ensembles of elastic distance measures

Several alternative distance measures for comparing time series have recently been proposed and evaluated on time series classification (TSC) problems. These include variants of dynamic time warping (DTW), such as weighted and derivative DTW, and edit distance-based measures, including longest common subsequence, edit distance with real penalty, time warp with edit, and move–split–merge. These measures have the common characteristic that they operate in the time domain and compensate for potential localised misalignment through some elastic adjustment. Our aim is to experimentally test two hypotheses related to these distance measures. Firstly, we test whether there is any significant difference in accuracy for TSC problems between nearest neighbour classifiers using these distance measures. Secondly, we test whether combining these elastic distance measures through simple ensemble schemes gives significantly better accuracy. We test these hypotheses by carrying out one of the largest experimental studies ever conducted into time series classification. Our first key finding is that there is no significant difference between the elastic distance measures in terms of classification accuracy on our data sets. Our second finding, and the major contribution of this work, is to define an ensemble classifier that significantly outperforms the individual classifiers. We also demonstrate that the ensemble is more accurate than approaches not based in the time domain. Nearly all TSC papers in the data mining literature cite DTW (with warping window set through cross validation) as the benchmark for comparison. We believe that our ensemble is the first ever classifier to significantly outperform DTW and as such raises the bar for future work in this area

Evaluation of the suitability of the Waterloo Membrane Sampler for sample preconcentration before compound-specific isotope analysis

Compound-specific isotope analysis (CSIA) has been used extensively for fingerprinting applications and for the evaluation of the degradation processes in organic contaminant studies in groundwater. Recently, the potential applications of CSIA in unsaturated and vapour intrusion studies have been explored. A key challenge in these studies is the development of analytical protocols for CSIA that can handle the very low concentrations of organic compounds typically found in the unsaturated zone and indoor samples. The objective of this research was to evaluate the applicability of the Waterloo Membrane Sampler (WMS) for CSIA, with intended applications in the unsaturated zone and in vapour intrusion studies. Tests were performed to evaluate isotope effects associated with sorption and desorption of the analytes under active sampling and passive sampling conditions. A standard gas mixture containing three model analytes, hexane, benzene and trichloroethene, was used in the experiments. Tests were designed to evaluate the isotope effect as a function of the time of exposure (3 to 192 hours), amount of analytes sorbed, and exposure temperature (25°C and 12°C). The results obtained in all studies showed very good reproducibility with standard deviations within the accepted analytical error of ±0.5 ‰. The data also showed that the δ13C values of the analytes collected by passive sampling were more depleted than the values obtained by active sampling. However, the degree of fractionation, ranging from 0.4 to 1.4 ‰, was practically constant and independent of the sampling time, mass adsorbed and temperature in the ranges of variables studied. The lowest concentrations that could be detected were 0.65mg/m3for hexane, 0.88mg/m3benzene and 4.38mg/m3for TCE. The method developed was applied in a field study where the results obtained for benzene and toluene collected in the unsaturated zone showed the expected values compared to carbon isotope data obtained for benzene and toluene at the water table. Results obtained in this study confirmed good data reproducibility. This indicates that CSIA coupled with WMS has the potential to become a valuable tool in unsaturated zone studies and in the environmental forensics field

The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances

In the last five years there have been a large number of new time series classification algorithms proposed in the literature. These algorithms have been evaluated on subsets of the 47 data sets in the University of California, Riverside time series classification archive. The archive has recently been expanded to 85 data sets, over half of which have been donated by researchers at the University of East Anglia. Aspects of previous evaluations have made comparisons between algorithms difficult. For example, several different programming languages have been used, experiments involved a single train/test split and some used normalised data whilst others did not. The relaunch of the archive provides a timely opportunity to thoroughly evaluate algorithms on a larger number of datasets. We have implemented 18 recently proposed algorithms in a common Java framework and compared them against two standard benchmark classifiers (and each other) by performing 100 resampling experiments on each of the 85 datasets. We use these results to test several hypotheses relating to whether the algorithms are significantly more accurate than the benchmarks and each other. Our results indicate that only 9 of these algorithms are significantly more accurate than both benchmarks and that one classifier, the Collective of Transformation Ensembles, is significantly more accurate than all of the others. All of our experiments and results are reproducible: we release all of our code, results and experimental details and we hope these experiments form the basis for more rigorous testing of new algorithms in the future

Study on Phylogenetic Relationships, Variability, and Correlated Mutations in M2 Proteins of Influenza Virus A

M2 channel, an influenza virus transmembrane protein, serves as an important target for antiviral drug design. There are still discordances concerning the role of some residues involved in proton transfer as well as the mechanism of inhibition by commercial drugs. The viral M2 proteins show high conservativity; about 3/4 of the positions are occupied by one residue in over 95%. Nine M2 proteins from the H3N2 strain and possibly two proteins from H2N2 strains make a phylogenic cluster closely related to 2RLF. The variability range is limited to 4 residues/position with one exception. The 2RLF protein stands out by the presence of 2 serines at the positions 19 and 50, which are in most other M2 proteins occupied by cysteines. The study of correlated mutations shows that there are several positions with significant mutational correlation that have not been described so far as functionally important. That there are 5 more residues potentially involved in the M2 mechanism of action. The original software used in this work (Consensus Constructor, SSSSg, Corm, Talana) is freely accessible as stand-alone offline applications upon request to the authors. The other software used in this work is freely available online for noncommercial purposes at public services on bioinformatics such as ExPASy or NCBI. The study on mutational variability, evolutionary relationship, and correlated mutation presented in this paper is a potential way to explain more completely the role of significant factors in proton channel action and to clarify the inhibition mechanism by specific drugs

Biomimetic generation of the strongest known biomaterial found in limpet tooth

The biomaterial with the highest known tensile strength is a unique composite of chitin and goethite (α-FeO(OH)) present in teeth from the Common Limpet (Patella vulgata). A biomimetic based on limpet tooth, with corresponding high-performance mechanical properties is highly desirable. Here we report on the replication of limpet tooth developmental processes ex vivo, where isolated limpet tissue and cells in culture generate new biomimetic structures. Transcriptomic analysis of each developmental stage of the radula, the organ from which limpet teeth originate, identifies sequential changes in expression of genes related to chitin and iron processing. We quantify iron and chitin metabolic processes in the radula and grow isolated radula cells in vitro. Bioinspired material can be developed with electrospun chitin mineralised by conditioned media from cultured radula cells. Our results inform molecular processes behind the generation of limpet tooth and establish a platform for development of a novel biomimetic with comparable properties

Thermodynamic principles and implementations of quantum machines

The efficiency of cyclic heat engines is limited by the Carnot bound. This bound follows from the second law of thermodynamics and is attained by engines that operate between two thermal baths under the reversibility condition whereby the total entropy does not increase. By contrast, the efficiency of engines powered by quantum non-thermal baths has been claimed to surpass the thermodynamic Carnot bound. The key to understanding the performance of such engines is a proper division of the energy supplied by the bath to the system into heat and work, depending on the associated change in the system entropy and ergotropy. Due to their hybrid character, the efficiency bound for quantum engines powered by a non-thermal bath does not solely follow from the laws of thermodynamics. Hence, the thermodynamic Carnot bound is inapplicable to such hybrid engines. Yet, they do not violate the principles of thermodynamics. An alternative means of boosting machine performance is the concept of heat-to-work conversion catalysis by quantum non-linear (squeezed) pumping of the piston mode. This enhancement is due to the increased ability of the squeezed piston to store ergotropy. Since the catalyzed machine is fueled by thermal baths, it adheres to the Carnot bound. We conclude by arguing that it is not quantumness per se that improves the machine performance, but rather the properties of the baths, the working fluid and the piston that boost the ergotropy and minimize the wasted heat in both the input and the output.Comment: As a chapter of: F. Binder, L. A. Correa, C. Gogolin, J. Anders, and G. Adesso (eds.), "Thermodynamics in the quantum regime - Recent Progress and Outlook", (Springer International Publishing

Adaptative Potential of the Lactococcus Lactis IL594 Strain Encoded in Its 7 Plasmids

The extrachromosomal gene pool plays a significant role both in evolution and in the environmental adaptation of bacteria. The L. lactis subsp. lactis IL594 strain contains seven plasmids, named pIL1 to pIL7, and is the parental strain of the plasmid-free L. lactis IL1403, which is one of the best characterized lactococcal strains of LAB. Complete nucleotide sequences of pIL1 (6,382 bp), pIL2 (8,277 bp), pIL3 (19,244 bp), pIL4 (48,979), pIL5 (23,395), pIL6 (28,435 bp) and pIL7 (28,546) were established and deposited in the generally accessible database (GeneBank). Nine highly homologous repB-containing replicons, belonging to the lactococcal theta-type replicons, have been identified on the seven plasmids. Moreover, a putative region involved in conjugative plasmid mobilization was found on four plasmids, through identification of the presence of mob genes and/or oriT sequences. Detailed bioinformatic analysis of the plasmid nucleotide sequences provided new insight into the repertoire of plasmid-encoded functions in L. lactis, and indicated that plasmid genes from IL594 strain can be important for L. lactis adaptation to specific environmental conditions (e.g. genes coding for proteins involved in DNA repair or cold shock response) as well as for technological processes (e.g. genes encoding citrate and lactose utilization, oligopeptide transport, restriction-modification system). Moreover, global gene analysis indicated cooperation between plasmid- and chromosome-encoded metabolic pathways