Compressed AFM-IR hyperspectral nanoimaging

Infrared (IR) hyperspectral imaging is a powerful approach in the field of materials and life sciences. However, for the extension to modern sub-diffraction nanoimaging it still remains a highly inefficient technique, as it acquires data via inherent sequential schemes. Here, we introduce the mathematical technique of low-rank matrix reconstruction to the sub-diffraction scheme of atomic force microscopy-based infrared spectroscopy (AFM-IR), for efficient hyperspectral IR nanoimaging. To demonstrate its application potential, we chose the trypanosomatid unicellular parasites Leishmania species as a realistic target of biological importance. The mid-IR spectral fingerprint window covering the spectral range from 1300 to 1900 cm−1 was chosen and a distance between the data points of 220 nm was used for nanoimaging of single parasites. The method of k-means cluster analysis was used for extracting the chemically distinct spatial locations. Subsequently, we randomly selected only 10% of an originally gathered data cube of 134 (x) × 50 (y) × 148 (spectral) AFM-IR measurements and completed the full data set by low-rank matrix reconstruction. This approach shows agreement in the cluster regions between full and reconstructed data cubes. Furthermore, we show that the results of the low-rank reconstruction are superior compared to alternative interpolation techniques in terms of error-metrics, cluster quality, and spectral interpretation for various subsampling ratios. We conclude that by using low-rank matrix reconstruction the data acquisition time can be reduced from more than 14 h to 1–2 h. These findings can significantly boost the practical applicability of hyperspectral nanoimaging in both academic and industrial settings involving nano- and bio-materials

Individual identification via electrocardiogram analysis

Background: During last decade the use of ECG recordings in biometric recognition studies has increased. ECG characteristics made it suitable for subject identification: it is unique, present in all living individuals, and hard to forge. However, in spite of the great number of approaches found in literature, no agreement exists on the most appropriate methodology. This study aimed at providing a survey of the techniques used so far in ECG-based human identification. Specifically, a pattern recognition perspective is here proposed providing a unifying framework to appreciate previous studies and, hopefully, guide future research. Methods: We searched for papers on the subject from the earliest available date using relevant electronic databases (Medline, IEEEXplore, Scopus, and Web of Knowledge). The following terms were used in different combinations: electrocardiogram, ECG, human identification, biometric, authentication and individual variability. The electronic sources were last searched on 1st March 2015. In our selection we included published research on peer-reviewed journals, books chapters and conferences proceedings. The search was performed for English language documents. Results: 100 pertinent papers were found. Number of subjects involved in the journal studies ranges from 10 to 502, age from 16 to 86, male and female subjects are generally present. Number of analysed leads varies as well as the recording conditions. Identification performance differs widely as well as verification rate. Many studies refer to publicly available databases (Physionet ECG databases repository) while others rely on proprietary recordings making difficult them to compare. As a measure of overall accuracy we computed a weighted average of the identification rate and equal error rate in authentication scenarios. Identification rate resulted equal to 94.95 % while the equal error rate equal to 0.92 %. Conclusions: Biometric recognition is a mature field of research. Nevertheless, the use of physiological signals features, such as the ECG traits, needs further improvements. ECG features have the potential to be used in daily activities such as access control and patient handling as well as in wearable electronics applications. However, some barriers still limit its growth. Further analysis should be addressed on the use of single lead recordings and the study of features which are not dependent on the recording sites (e.g. fingers, hand palms). Moreover, it is expected that new techniques will be developed using fiducials and non-fiducial based features in order to catch the best of both approaches. ECG recognition in pathological subjects is also worth of additional investigations

Magnetic detection of injury-induced ionic currents in bean plants.

A superconducting quantum interference device (SQUID) multichannel magnetometer was used to measure the temporal and spatial evolution of the magnetic field accompanying stimulation by burning and/or cutting of Vicia faba plants. These magnetic fields are caused by ionic currents that appear after injury in different parts of the plant. All measured V. faba plants responded to the burning stimulation with detectable quasi-d.c. magnetic signals. In order to measure these signals, a suitable modulation had to be used. The covariance method was applied to analyse the measured data. The results demonstrate a dipolar-like magnetic signal, exponentially decreasing in time, above the cutting type of injury. After the burning stimulation, the magnetically detected activity was concentrated predominantly above the leaves/petioles and less above the stem. Possible mechanisms for this behaviour are suggested. A comparison with previously known electrical measurements of plant injury is given

Spatial and temporal distribution of magnetic field due to injury currents in Vicia faba plants

Introduction Different types of wounds on plants cause measureable changes in the biochemical and biophysical behaviour of plants. Among them are also electrophysiological changes. Studies using extracellular and intracellular electrodes have revealed that wounding of tissue causes in a variety of plants changes in the electrical membrane voltage e.g. [1, 2, 3, 4]. Typically, the electrical response consists of a rapid action potential-like depolarization followed by a slower long lasting depolarization usually termed the variation potential. The elementary basis of these transient voltage changes is not yet known. It has been speculated, that the fast transient depolarization is an action potential and is therefore propagated - just as in nerve cells - as a true long distance electrical signal [2]. The slow voltage transient on the other hand might be the consequence of chemical signals which are distributed via the xylem [5]. Wounding induced voltage changes are transmitted from th